Applied Intelligence and Informatics
This book constitutes the refereed proceedings of the First International Conference on Applied Intelligence and Informatics, AII 2021, held in Nottingham, UK, in July 2021. Due to the COVID-19 pandemic the conference was held in a fully virtual mode. The 26 full papers and 4 short papers presented were thoroughly reviewed and selected from the total 107 submissions. They are organized in the following topical sections: application of AI and informatics in disease detection; application of AI and informatics in healthcare; application of AI and informatics in pattern recognition; application of AI and informatics in network, security, and analytics; emerging applications of AI and informatics.
Text Mining
This book comprises a set of articles that specify the methodology of text mining, describe the creation of lexical resources in the framework of text mining and use text mining for various tasks in natural language processing (NLP). The analysis of large amounts of textual data is a prerequisite to build lexical resources such as dictionaries and ontologies and also has direct applications in automated text processing in fields such as history, healthcare and mobile applications, just to name a few. This volume gives an update in terms of the recent gains in text mining methods and reflects the most recent achievements with respect to the automatic build-up of large lexical resources. It addresses researchers that already perform text mining, and those who want to enrich their battery of methods. Selected articles can be used to support graduate-level teaching.The book is suitable for all readers that completed undergraduate studies of computational linguistics, quantitativelinguistics, computer science and computational humanities. It assumes basic knowledge of computer science and corpus processing as well as of statistics.
Data and Information in Online Environments
This book constitutes the refereed post-conference proceedings of the Second International Conference on Data Information in Online Environments, DIONE 2021, which took place in March 2021. Due to COVID-19 pandemic the conference was held virtually. DIONE 2021 presents theoretical proposals and practical solutions in the treatment, processing and study of data and information produced in online environments, the latest trends in the analysis of network information, media metrics social, data processing technologies and open science. The 40 revised full papers were carefully reviewed and selected from 86 submissions. The papers are grouped in thematical sessions on evaluation of science in social networking environment; scholarly publishing and online communication; and education in online environments.
Mathematical Optimization Theory and Operations Research
This book constitutes the proceedings of the 20th International Conference on Mathematical Optimization Theory and Operations Research, MOTOR 2021, held in Irkutsk, Russia, in July 2021. The 29 full papers and 1 short paper presented in this volume were carefully reviewed and selected from 102 submissions. Additionally, 2 full invited papers are presented in the volume. The papers are grouped in the following topical sections: ​combinatorial optimization; mathematical programming; bilevel optimization; scheduling problems; game theory and optimal control; operational research and mathematical economics; data analysis.
Artificial Intelligence and Security
This two-volume set of LNCS 12736-12737 constitutes the refereed proceedings of the 7th International Conference on Artificial Intelligence and Security, ICAIS 2021, which was held in Dublin, Ireland, in July 2021. The conference was formerly called "International Conference on Cloud Computing and Security" with the acronym ICCCS.The total of 93 full papers and 29 short papers presented in this two-volume proceedings was carefully reviewed and selected from 1013 submissions. Overall, a total of 224 full and 81 short papers were accepted for ICAIS 2021; the other accepted papers are presented in CCIS 1422-1424. The papers were organized in topical sections as follows: Part I: Artificial intelligence; and big data Part II: Big data; cloud computing and security; encryption and cybersecurity; information hiding; IoT security; and multimedia forensics
Intelligent Information Systems
This book constitutes the thoroughly refereed proceedings of the CAiSE Forum 2021 which was held as part of the 33rd International Conference on Advanced Information Systems Engineering, CAiSE 2021, in June 2021. The conference was held virtually due to the COVID-19 pandemic.The CAiSE Forum is a place within the CAiSE conference for presenting and discussing new ideas and tools related to information systems engineering. Intended to serve as an interactive platform, the Forum aims at the presentation of emerging new topics and controversial positions, as well as demonstration of innovative systems, tools and applications. This year's theme was "Intelligent Information Systems".The 18 full papers presented in this volume were carefully reviewed and selected for inclusion in this book.
Integration of Constraint Programming, Artificial Intelligence, and Operations Research
This volume LNCS 12735 constitutes the papers of the 18th International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, CPAIOR 2021, which was held in Vienna, Austria, in 2021. Due to the COVID-19 pandemic the conference was held online. The 30 regular papers presented were carefully reviewed and selected from a total of 75 submissions. The conference program included a Master Class on the topic "Explanation and Verification of Machine Learning Models".
97 Things Every Data Engineer Should Know
Take advantage of today's sky-high demand for data engineers. With this in-depth book, current and aspiring engineers will learn powerful real-world best practices for managing data big and small. Contributors from notable companies including Twitter, Google, Stitch Fix, Microsoft, Capital One, and LinkedIn share their experiences and lessons learned for overcoming a variety of specific and often nagging challenges. Edited by Tobias Macey, host of the popular Data Engineering Podcast, this book presents 97 concise and useful tips for cleaning, prepping, wrangling, storing, processing, and ingesting data. Data engineers, data architects, data team managers, data scientists, machine learning engineers, and software engineers will greatly benefit from the wisdom and experience of their peers. Topics include: The Importance of Data Lineage - Julien Le Dem Data Security for Data Engineers - Katharine Jarmul The Two Types of Data Engineering and Data Engineers - Jesse Anderson Six Dimensions for Picking an Analytical Data Warehouse - Gleb Mezhanskiy The End of ETL as We Know It - Paul Singman Building a Career as a Data Engineer - Vijay Kiran Modern Metadata for the Modern Data Stack - Prukalpa Sankar Your Data Tests Failed! Now What? - Sam Bail
Enterprise, Business-Process and Information Systems Modeling
This book contains the proceedings of two long-running events held along with the CAiSE conference relating to the areas of enterprise, business-process and information systems modeling: * the 22nd International Conference on Business Process Modeling, Development and Support, BPMDS 2021, and * the 26th International Conference on Exploring Modeling Methods for Systems Analysis and Development, EMMSAD 2021. The conferences were planned to take place in Melbourne, Australia, during June 28-29, 2021, but changed to an online format due to the COVID-19 pandemic. For BPMDS 10 full papers and 1 short paper were carefully reviewed and selected for publication from a total of 26 submissions; for EMMSAD 13 full papers and 1 short paper were accepted from 34 submissions. The papers were organized in topical sections as follows: BPMDS: Improving event data quality in coherence with business requirements; enhancing the value of data in processesimprovement; event stream and predictive monitoring; modeling languages and reference models; EMMSAD: Enterprise modeling; handling models and modeling methods; threat and evidence modeling; and model-driven engineering and applications.
Mastering spaCy
Build end-to-end industrial-strength NLP models using advanced morphological and syntactic features in spaCy to create real-world applications with easeKey Features: Gain an overview of what spaCy offers for natural language processingLearn details of spaCy's features and how to use them effectivelyWork through practical recipes using spaCyBook Description: spaCy is an industrial-grade, efficient NLP Python library. It offers various pre-trained models and ready-to-use features. Mastering spaCy provides you with end-to-end coverage of spaCy's features and real-world applications.You'll begin by installing spaCy and downloading models, before progressing to spaCy's features and prototyping real-world NLP apps. Next, you'll get familiar with visualizing with spaCy's popular visualizer displaCy. The book also equips you with practical illustrations for pattern matching and helps you advance into the world of semantics with word vectors. Statistical information extraction methods are also explained in detail. Later, you'll cover an interactive business case study that shows you how to combine all spaCy features for creating a real-world NLP pipeline. You'll implement ML models such as sentiment analysis, intent recognition, and context resolution. The book further focuses on classification with popular frameworks such as TensorFlow's Keras API together with spaCy. You'll cover popular topics, including intent classification and sentiment analysis, and use them on popular datasets and interpret the classification results.By the end of this book, you'll be able to confidently use spaCy, including its linguistic features, word vectors, and classifiers, to create your own NLP apps.What You Will Learn: Install spaCy, get started easily, and write your first Python scriptUnderstand core linguistic operations of spaCyDiscover how to combine rule-based components with spaCy statistical modelsBecome well-versed with named entity and keyword extractionBuild your own ML pipelines using spaCyApply all the knowledge you've gained to design a chatbot using spaCyWho this book is for: This book is for data scientists and machine learners who want to excel in NLP as well as NLP developers who want to master spaCy and build applications with it. Language and speech professionals who want to get hands-on with Python and spaCy and software developers who want to quickly prototype applications with spaCy will also find this book helpful. Beginner-level knowledge of the Python programming language is required to get the most out of this book. A beginner-level understanding of linguistics such as parsing, POS tags, and semantic similarity will also be useful.
Econometrics in Practice
No detailed description available for "Econometrics in Practice".
Implementing Power BI in the Enterprise
Power BI is an amazing tool. It's so easy to get started with and to develop a proof of concept. Enterprises want more than that. They need to create analytics using professional techniques. In this unique book, Dr Greg Low shows you how he has implemented many successful Power BI implementations in enterprises.If you want a book on building better visualizations in Power BI, this is not the book for you. Instead, this book will teach you about architecture, identity and security, building a supporting data warehouse, using DevOps and project management tools, learning to use Azure Data Factory and source control with your projects. It also describes how he implements projects for clients with differing levels of cloud tolerance, from the cloud natives, to cloud friendlies, to cloud conservatives, and to those clients who are not cloud friendly at all.
Guide to Discrete Mathematics
This stimulating textbook presents a broad and accessible guide to the fundamentals of discrete mathematics, highlighting how the techniques may be applied to various exciting areas in computing. The text is designed to motivate and inspire the reader, encouraging further study in this important skill. Features: This book provides an introduction to the building blocks of discrete mathematics, including sets, relations and functions; describes the basics of number theory, the techniques of induction and recursion, and the applications of mathematical sequences, series, permutations, and combinations; presents the essentials of algebra; explains the fundamentals of automata theory, matrices, graph theory, cryptography, coding theory, language theory, and the concepts of computability and decidability; reviews the history of logic, discussing propositional and predicate logic, as well as advanced topics such as the nature of theorem proving; examines the field of software engineering, including software reliability and dependability and describes formal methods; investigates probability and statistics and presents an overview of operations research and financial mathematics.
Data-Centric Business and Applications
Van der Pol Oscillators Based on Transistor Structures with Negative Differential Resistance for Infocommunication System Facilities.- Study of the Influence of Changing Signal Propagation Conditions in the Communication Channel on Bit Error Rate.- Quality Assessment of Measuring the Coordinates of Airborne Objects with a Secondary Surveillance Radar.- Pulse and Multifrequency Van der Pol Generators Based on Transistor Structures with Negative Differential Resistance for Infocommunication System Facilities.- The Method of Redistributing Traffic in Mobile Network.- Complex Tools for Surge Process Analysis and Hardware Disturbance Protection.- Development of Evaluation Templates for the Protection System of Wireless Sensor Network.- Studying of Useful Signal Impact on Convergence Parameters of the Gradient Signal Processing Algorithm for Adaptive Antenna Arrays that Obviates Reference Signal Presence.- Interference Immunity Assessment Identification Friend or Foe Systems.- Estimation of Signal Parameters Using SSA and Linear Transformation of Covariance Matrix or Data Matrix.
Machine Learning and Iot for Intelligent Systems and Smart Applications
This book discusses algorithmic applications in the field of machine learning and IOT with pertinent applications. It further discusses challenges and future directions in the machine learning area and develops understanding of its role in technology, in terms of IoT security issues. It includes pertinent applications and case studies.
Advanced Information Systems Engineering Workshops
This book constitutes the thoroughly refereed proceedings of the international workshops associated with the 33rd International Conference on Advanced Information Systems Engineering, CAiSE 2021, which was held during June 28-July 2, 2021. The conference was planned to take place in Melbourne, Australia, but changed to an online format due to the COVID-19 pandemic. The workshops included in this volume are: - BC4IS: 1st International Workshop on Blockchain for Information Systems- EMoBI: 3rd International Workshop on Ethics and Morality in Business Informatics- KET4DF: 3rd International Workshop on Key Enabling Technology for Digital Factories- MOBA: 1st International Workshop on Model-driven Organizational and Business Agility- NeGIS: 2nd International Workshop on Next Generation Information SystemsThey focus on topics and trends ranging from blockchain technologies to digital factories, ethics, and business agility to the next generation of information systems.The 14 full papers and 1 short paper presented in this volume were carefully reviewed and selected from 33 submissions.
Machine Learning with the Elastic Stack - Second Edition
Discover expert techniques for combining machine learning with the analytic capabilities of Elastic Stack and uncover actionable insights from your dataKey Features: Integrate machine learning with distributed search and analyticsPreprocess and analyze large volumes of search data effortlesslyOperationalize machine learning in a scalable, production-worthy wayBook Description: Elastic Stack, previously known as the ELK stack, is a log analysis solution that helps users ingest, process, and analyze search data effectively. With the addition of machine learning, a key commercial feature, the Elastic Stack makes this process even more efficient. This updated second edition of Machine Learning with the Elastic Stack provides a comprehensive overview of Elastic Stack's machine learning features for both time series data analysis as well as for classification, regression, and outlier detection.The book starts by explaining machine learning concepts in an intuitive way. You'll then perform time series analysis on different types of data, such as log files, network flows, application metrics, and financial data. As you progress through the chapters, you'll deploy machine learning within Elastic Stack for logging, security, and metrics. Finally, you'll discover how data frame analysis opens up a whole new set of use cases that machine learning can help you with.By the end of this Elastic Stack book, you'll have hands-on machine learning and Elastic Stack experience, along with the knowledge you need to incorporate machine learning in your distributed search and data analysis platform.What You Will Learn: Find out how to enable the ML commercial feature in the Elastic StackUnderstand how Elastic machine learning is used to detect different types of anomalies and make predictionsApply effective anomaly detection to IT operations, security analytics, and other use casesUtilize the results of Elastic ML in custom views, dashboards, and proactive alertingTrain and deploy supervised machine learning models for real-time inferenceDiscover various tips and tricks to get the most out of Elastic machine learningWho this book is for: If you're a data professional looking to gain insights into Elasticsearch data without having to rely on a machine learning specialist or custom development, then this Elastic Stack machine learning book is for you. You'll also find this book useful if you want to integrate machine learning with your observability, security, and analytics applications. Working knowledge of the Elastic Stack is needed to get the most out of this book.
Natural Language Processing and Information Systems
This book constitutes the refereed proceedings of the 26th International Conference on Applications of Natural Language to Information Systems, NLDB 2021, held online in July 2021. The 19 full papers and 14 short papers were carefully reviewed and selected from 82 submissions. The papers are organized in the following topical sections: role of learning; methodological approaches; semantic relations; classification; sentiment analysis; social media; linking documents; multimodality; applications.
Communicating with Data Visualisation
How can you transform a spreadsheet of numbers into a clear, compelling story that your audience will want to pass on?This book is a step-by-step guide (honed through the authors' Guardian masterclasses, workshops and seminars) to bringing data to life through visualisations, from static charts and maps to interactive infographics and motion graphics.Introducing a four-step framework to creating engaging and innovative visualisations, it helps you to: - Find the human stories in your datasets- Design a visual story that will resonate with your audience- Make a clear, persuasive visual that represents your data truthfully- Refine your work to ensure your visual expresses your story in the best possible way.This book also includes a portfolio of best-practice examples and annotated templates to help you choose the right visual for the right audience, and repurpose your work for different contexts.
Social, Cultural, and Behavioral Modeling
This book constitutes the proceedings of the 14th International Conference on Social, Cultural, and Behavioral Modeling, SBP-BRiMS 2021, which was held online during July 6-9, 2021.The 32 full papers presented in this volume were carefully reviewed and selected from 56 submissions. The papers were organized in topical sections as follows: COVID-related focus; methodologies; social cybersecurity and social networks; and human and agent modeling. They represent a wide number of disciplines including computer science, psychology, sociology, communication science, public health, bioinformatics, political science, and organizational science. Numerous types of computational methods are used including, but not limited to, machine learning, language technology, social network analysis and visualization, agent-based simulation, and statistics.
Service-Oriented Computing - Icsoc 2020 Workshops
This book constitutes revised and selected papers from the scientific satellite events held in conjunction with the18th International Conference on Service-Oriented Computing, ICSOC 2020. The conference was held virtually during December 14-17, 2020. A total of 125 submissions were received for the satellite events. The volume includes 9 papers from the PhD Symposium Track, 4 papers from the Demonstration Track, and 45 papers from the following workshops: International Workshop on Artificial Intelligence for IT Operations (AIOps)International Workshop on Cyber Forensics and Threat Investigations Challenges in Emerging Infrastructures (CFTIC 2020)2nd Workshop on Smart Data Integration and Processing (STRAPS 2020)International Workshop on AI-enabled Process Automation (AI-PA 2020)International Workshop on Artificial Intelligence in the IoT Security Services (AI-IOTS 2020)
Design, Operation and Evaluation of Mobile Communications
This conference proceeding LNCS 12796 constitutes the thoroughly refereed proceedings of the 2nd International Conference on Design, Operation and Evaluation of Mobile Communications, MOBILE 2021 which was held as part of the 23rd HCI International Conference, HCII 2021 as a virtual event, due to COVID-19, in July 2021. The total of 1276 papers and 241 posters included in the 39 HCII 2021 proceedings volumes were carefully reviewed and selected from 5222 submissions. MOBILE 2021 includes a total of 27 papers; they were organized in topical sections named: Designing, Developing and Evaluating Mobile Interaction Systems and User Experience, Acceptance and Impact of Mobile Communications.
Theoremus
A compact and easily accessible book, it guides the reader in unravelling the apparent mysteries found in doing mathematical proofs. Simply written, it introduces the art and science of proving mathematical theorems and propositions and equips students with the skill required to tackle the task of proving mathematical assertions. Theoremus - A Student's Guide to Mathematical Proofs is divided into two parts. Part 1 provides a grounding in the notion of mathematical assertions, arguments and fallacies and Part 2, presents lessons learned in action by applying them into the study of logic itself. The book supplies plenty of examples and figures, gives some historical background on personalities that gave rise to the topic and provides reflective problems to try and solve. The author aims to provide the reader with the confidence to take a deep dive into some more advanced work in mathematics or logic.
Mobility Data-Driven Urban Traffic Monitoring
This book introduces the concepts of mobility data and data-driven urban traffic monitoring. A typical framework of mobility data-based urban traffic monitoring is also presented, and it describes the processes of mobility data collection, data processing, traffic modelling, and some practical issues of applying the models for urban traffic monitoring. This book presents three novel mobility data-driven urban traffic monitoring approaches. First, to attack the challenge of mobility data sparsity, the authors propose a compressive sensing-based urban traffic monitoring approach. This solution mines the traffic correlation at the road network scale and exploits the compressive sensing theory to recover traffic conditions of the whole road network from sparse traffic samplings. Second, the authors have compared the traffic estimation performances between linear and nonlinear traffic correlation models and proposed a dynamical non-linear traffic correlation modelling-basedurban traffic monitoring approach. To address the challenge of involved huge computation overheads, the approach adapts the traffic modelling and estimations tasks to Apache Spark, a popular parallel computing framework. Third, in addition to mobility data collected by the public transit systems, the authors present a crowdsensing-based urban traffic monitoring approach. The proposal exploits the lightweight mobility data collected from participatory bus riders to recover traffic statuses through careful data processing and analysis. Last but not the least, the book points out some future research directions, which can further improve the accuracy and efficiency of mobility data-driven urban traffic monitoring at large scale.This book targets researchers, computer scientists, and engineers, who are interested in the research areas of intelligent transportation systems (ITS), urban computing, big data analytic, and Internet of Things (IoT). Advanced level students studying these topics benefit from this book as well.
Mastering Tableau 2021- Third Edition
Build, design, and improve advanced business intelligence solutions using Tableau's latest features, including Tableau Prep Builder, Tableau Hyper, and Tableau ServerKey Features: Master new features in Tableau 2021 to solve real-world analytics challengesPerform geo-spatial, time series, and self-service analytics using real-life examplesBuild and publish dashboards and explore storytelling using Python and R integration supportBook Description: Tableau is one of the leading business intelligence (BI) tools used to solve data analysis challenges. With this book, you will master Tableau's features and offerings in various paradigms of the BI domain.Updated with fresh topics including Quick Level of Detail expressions, the newest Tableau Server features, Einstein Discovery, and more, this book covers essential Tableau concepts and advanced functionalities. Leveraging Tableau Hyper files and using Prep Builder, you'll be able to perform data preparation and handling easily. You'll gear up to perform complex joins, spatial joins, unions, and data blending tasks using practical examples. Following this, you'll learn how to execute data densification and further explore expert-level examples to help you with calculations, mapping, and visual design using Tableau extensions. You'll also learn about improving dashboard performance, connecting to Tableau Server and understanding data visualization with examples. Finally, you'll cover advanced use cases such as self-service analysis, time series analysis, and geo-spatial analysis, and connect Tableau to Python and R to implement programming functionalities within Tableau.By the end of this Tableau book, you'll have mastered the advanced offerings of Tableau 2021 and be able to tackle common and advanced challenges in the BI domain.What You Will Learn: Get up to speed with various Tableau componentsMaster data preparation techniques using Tableau Prep BuilderDiscover how to use Tableau to create a PowerPoint-like presentationUnderstand different Tableau visualization techniques and dashboard designsInteract with the Tableau server to understand its architecture and functionalitiesStudy advanced visualizations and dashboard creation techniquesBrush up on powerful self-service analytics, time series analytics, and geo-spatial analyticsWho this book is for: This book is designed for business analysts, business intelligence professionals and data analysts who want to master Tableau to solve a range of data science and business intelligence problems. The book is ideal if you have a good understanding of Tableau and want to take your skills to the next level.
Distributed, Ambient and Pervasive Interactions
This conference proceedings LNCS 12782 constitutes the refereed proceedings of the 9 th International Conference on Distributed, Ambient and Pervasive Interactions, DAPI 2021, held as part of the 23rd International Conference, HCI International 2021, which took place in July 2021. The conference was held virtually due to the COVID-19 pandemic.The total of 1276 papers and 241 posters included in the 39 HCII 2021 proceedings volumes was carefully reviewed and selected from 5222 submissions. The papers of DAPI 2021, Distributed, Ambient and Pervasive Interactions, are organized in topical sections named: Smart Cities; IoT, Sensors and Smart Environments; Learning and Culture in Intelligent Environments; Designing Intelligent Environments.
Business Modeling and Software Design
This book constitutes the refereed proceedings of the 11th International Symposium on Business Modeling and Software Design, BMSD 2021, which took place in Sofia, Bulgaria, in July 2021.The 14 full and 13 short papers included in this book were carefully reviewed and selected from a total of 61 submissions. BMSD is a leading international forum that brings together researchers and practitioners interested in business modeling and its relation to software design. Particular areas of interest are: Business Processes and Enterprise Engineering; Business Models and Requirements; Business Models and Services; Business Models and Software; Information Systems Architectures and Paradigms; Data Aspects in Business Modeling and Software Development; Blockchain-Based Business Models and Information Systems; IoT and Implications for Enterprise Information Systems. The BMSD 2021 theme was: Towards Enterprises and Software that are Resilient against Disruptive Events.
From Opinion Mining to Financial Argument Mining
Opinion mining is a prevalent research issue in many domains. In the financial domain, however, it is still in the early stages. Most of the researches on this topic only focus on the coarse-grained market sentiment analysis, i.e., 2-way classification for bullish/bearish. Thanks to the recent financial technology (FinTech) development, some interdisciplinary researchers start to involve in the in-depth analysis of investors' opinions. These works indicate the trend toward fine-grained opinion mining in the financial domain. When expressing opinions in finance, terms like bullish/bearish often spring to mind. However, the market sentiment of the financial instrument is just one type of opinion in the financial industry. Like other industries such as manufacturing and textiles, the financial industry also has a large number of products. Financial services are also a major business for many financial companies, especially in the context of the recent FinTech trend. For instance, many commercial banks focus on loans and credit cards. Although there are a variety of issues that could be explored in the financial domain, most researchers in the AI and NLP communities only focus on the market sentiment of the stock or foreign exchange. This open access book addresses several research issues that can broaden the research topics in the AI community. It also provides an overview of the status quo in fine-grained financial opinion mining to offer insights into the futures goals. For a better understanding of the past and the current research, it also discusses the components of financial opinions one-by-one with the related works and highlights some possible research avenues, providing a research agenda with both micro- and macro-views toward financial opinions.
The Once-Only Principle
This open access State-of-the-Art Survey describes and documents the developments and results of the Once-Only Principle Project (TOOP). The Once-Only Principle (OOP) is part of the seven underlying principles of the eGovernment Action Plan 2016-2020. It aims to make the government more effective and to reduce administrative burdens by asking citizens and companies to provide certain standard information to the public authorities only once.The project was horizontal and policy-driven with the aim of showing that the implementation of OOP in a cross-border and cross-sector setting is feasible. The book summarizes the results of the project from policy, organizational, architectural, and technical points of view.
Transactions on Large-Scale Data- And Knowledge-Centered Systems XLVIII
The LNCS journal Transactions on Large-Scale Data- and Knowledge-Centered Systems focuses on data management, knowledge discovery, and knowledge processing, which are core and hot topics in computer science. Since the 1990s, the Internet has become the main driving force behind application development in all domains. An increase in the demand for resource sharing (e.g., computing resources, services, metadata, data sources) across different sites connected through networks has led to an evolution of data- and knowledge management systems from centralized systems to decentralized systems enabling large-scale distributed applications providing high scalability. This, the 48th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains 8 invited papers dedicated to the memory of Prof. Dr. Roland Wagner. The topics covered include distributed database systems, NewSQL, scalable transaction management, strong consistency, caches, data warehouse, ETL, reinforcement learning, stochastic approximation, multi-agent systems, ontology, model-driven development, organisational modelling, digital government, new institutional economics and data governance.
Geographical Information Systems Theory, Applications and Management
This book constitutes selected, revised and extended papers of the 6th International Conference on Geographical Information Systems Theory, Applications and Management, GISTAM 2020, held in Prague, Czech Republic, May 2020. Due to the COVID-19 pandemic the conference was held online. The 9 revised full papers presented were carefully reviewed and selected from 62 submissions. The papers are centered on urban and regional planning; water information systems; geospatial information and technologies; spatio-temporal database management; decision support systems; energy information systems; GPS and location detection.
Business Intelligence
Decision support, information systems and NLP (full papers).- Part-of-Speech Tagging using Long Short Term Memory (LSTM): Amazigh text writ-ten in Tifinaghe characters.- Contribution to Arabic Text Classification using Machine Learning Techniques.- Analyzing Moroccan Tweets to Extract Sentiments Related to the Coronavirus Pandemic: A New Classification Approach.- Towards a support system for brainstorming based content-based information ex-traction and machine learning.- Classification of Documents using Machine Learning and Genetic Algorithms.- Toward Student Classification In Educational Video Courses Using Knowledge Tracing .- Assessment of lifestyle and mental health: case study of the FST Beni Mellal.- The search for digital information by evaluating four models.- Overview of the main recommendation approaches for the scientific articles.- Online students' classification based on the Formal Concepts analysis and multiple choice questions.- How BERT's dropout fine-tuning affects text classification.- Big data, Datamining, Web services & Web semantics (full papers).- Selection of Composite Web Services based on QoS.- A MapReduce Improved ID3 Decision Tree for Classifying Twitter Data.- Clustering techniques for Big Data Mining.- Data mining approach for intrusion detection.- Optimization and Decision support (full papers).- Markov Decision Processes with DiscountedRewards: New action elimination procedure.- Learning Management System comparison: new approach using Multi-Criteria Decision Making.- Finding agreements: Study and evaluation of heuristic approaches to multilateral negotiation.- Signal, Image and Vision Computing (full papers).- A new approach based on Steganography to face facial recognition vulnerabilities against Fake identities.- Mean Square Convergence of Reproducing Kernel For Channel Identification: Application to Bran D Channel Impulse Response.- Deep learning for medical image segmentation.- Networking, Cloud computing & Networking Architectures in Cloud (full papers).- Optimal Virtual Machine Provisioning in Cloud Computing Using Game Theory.- Comparative study between RFID readers anti-collision protocols in dense environments.- Game Theoretic Approaches to Mitigate Cloud Security Risks: An Initial Insight.- Comparative study on the McEliece Public-key Cryptosystem based on Goppa and QC-MDPC codes.- Optimization Of Leach Protocol For Saving Energie In Wireless Sensor Networks.- Big data, Datamining, Web services & Web semantics (poster papers).- Brain Cancer Ontology Construction.- Semantic Web for sharing medical resources.- Construction of glaucoma disease ontology.- Signal, Image and Vision Computing (poster papers).- Creation of a Callbot module for automatic processing of a customer service calls.- Applied CNN for automatic diabetic retinopathy assessment using Fundus Images.- RFID Based Security and Automatic Parking Access Control System.
Web Engineering
This book constitutes the proceedings of the 21st International Conference on Web Engineering, ICWE 2021, which was supposed to be held in Biarritz, France, in May 2021. Due to the corona pandemic the conference changed to a virtual format.The total of 22 full and 13 short contributions presented in this volume were carefully reviewed and selected from 128 submissions. The book also contains 6 demonstration, 1 poster, 3 PhD, and 3 tutorial papers. The papers were organized in topical sections named: Semantic Web; social Web; Web modeling and engineering; Web big data and data analytics; Web mining and knowledge extraction; Web of Things; Web programming; Web user interfaces; PhD symposium; posters and demonstrations; and tutorials.Chapter "A Web-Based Co-Creation and User Engagement Method and Platform" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Hands-On Kubernetes on Azure - Third Edition
Understand the fundamentals of Kubernetes deployment on Azure with a learn-by-doing approachKey Features: Get to grips with the fundamentals of containers and KubernetesDeploy containerized applications using the Kubernetes platformLearn how you can scale your workloads and secure your application running in Azure Kubernetes ServiceBook Description: Containers and Kubernetes containers facilitate cloud deployments and application development by enabling efficient versioning with improved security and portability.With updated chapters on role-based access control, pod identity, storing secrets, and network security in AKS, this third edition begins by introducing you to containers, Kubernetes, and Azure Kubernetes Service (AKS), and guides you through deploying an AKS cluster in different ways. You will then delve into the specifics of Kubernetes by deploying a sample guestbook application on AKS and installing complex Kubernetes apps using Helm. With the help of real-world examples, you'll also get to grips with scaling your applications and clusters.As you advance, you'll learn how to overcome common challenges in AKS and secure your applications with HTTPS. You will also learn how to secure your clusters and applications in a dedicated section on security. In the final section, you'll learn about advanced integrations, which give you the ability to create Azure databases and run serverless functions on AKS as well as the ability to integrate AKS with a continuous integration and continuous delivery (CI/CD) pipeline using GitHub Actions.By the end of this Kubernetes book, you will be proficient in deploying containerized workloads on Microsoft Azure with minimal management overhead.What You Will Learn: Plan, configure, and run containerized applications in production.Use Docker to build applications in containers and deploy them on Kubernetes.Monitor the AKS cluster and the application.Monitor your infrastructure and applications in Kubernetes using Azure Monitor.Secure your cluster and applications using azure-native security tools.Connect an app to the Azure database.Store your container images securely with Azure Container Registry.Install complex Kubernetes applications using Helm.Integrate Kubernetes with multiple Azure PaaS services, such as databases, Azure Security Center, and Functions.Use GitHub Actions to perform continuous integration and continuous delivery to your cluster.Who this book is for: If you are an aspiring DevOps professional, system administrator, developer, or site reliability engineer interested in learning how to get the most out of containers and Kubernetes, then this book is for you.
Advances in Knowledge Discovery and Data Mining
The 3-volume set LNAI 12712-12714 constitutes the proceedings of the 25th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2021, which was held during May 11-14, 2021.The 157 papers included in the proceedings were carefully reviewed and selected from a total of 628 submissions. They were organized in topical sections as follows: Part I: Applications of knowledge discovery and data mining of specialized data; Part II: Classical data mining; data mining theory and principles; recommender systems; and text analytics; Part III: Representation learning and embedding, and learning from data.
Artificial Intelligence and Security
This two-volume set of LNCS 12736-12737 constitutes the refereed proceedings of the 7th International Conference on Artificial Intelligence and Security, ICAIS 2021, which was held in Dublin, Ireland, in July 2021. The conference was formerly called "International Conference on Cloud Computing and Security" with the acronym ICCCS.The total of 93 full papers and 29 short papers presented in this two-volume proceedings was carefully reviewed and selected from 1013 submissions. Overall, a total of 224 full and 81 short papers were accepted for ICAIS 2021; the other accepted papers are presented in CCIS 1422-1424. The papers were organized in topical sections as follows: Part I: Artificial intelligence; and big data Part II: Big data; cloud computing and security; encryption and cybersecurity; information hiding; IoT security; and multimedia forensics
Research Challenges in Information Science
This book constitutes the proceedings of the 15th International Conference on Research Challenges in Information Sciences, RCIS 2021, which was planned to take place in Limassol, Cyprus, but had to change to an online event due to the COVID-19 pandemic. The conference took place virtually during May 11-14, 2021. It focused on the special theme "Information Science and Global Crisis".The scope of RCIS is summarized by the thematic areas of information systems and their engineering; user-oriented approaches; data and information management; business process management; domain-specific information systems engineering; data science; information infrastructures, and reflective research and practice.The 29 full papers and 6 work-in-progress papers presented in this volume were carefully reviewed and selected from 99 submissions. They were organized in topical sections named: Business and Industrial Processes, Information Security and Risk Management, Data and Information Management, Domain-specific Information Systems Engineering, User-Centered Approaches, Data Science and Decision Support, and Information Systems and Their Engineering. The volume also contains 13 poster and demo papers, and 4 doctoral consortium papers. In addition, two-page summaries of tutorials and research project papers can be found in the back matter.
Closing the Analytics Talent Gap
Organizations recognize that universities are rich resource for closing their analytical talent gaps. The book addresses the benefits and challenges of working with university analytics and data science programs at the undergraduate, masters, and doctoral levels.
Logics in Artificial Intelligence
This book constitutes the proceedings of the 17th European Conference on Logics in Artificial Intelligence, JELIA 2021, held as a virtual event, in May 2021. The 27 full papers and 3 short papers included in this volume were carefully reviewed and selected from 68 submissions. The accepted papers span a number of areas within Logics in AI, including: argumentation; belief revision; reasoning about actions, causality, and change; constraint satisfaction; description logics and ontological reasoning; non-classical logics; and logic programming (answer set programming).
Data Governance
Data is fundamentally changing the nature of businesses and organisations and the mechanisms for delivering products and services. This book is a practical guide to developing strategy and policy for data governance, in line with the developing ISO 38505 governance of data standards. It will assist an organisation wanting to become more of a data driven business by explaining how to assess the value, risks and constraints associated with collecting, using and distributing data.
Information Refinement Technologies for Crisis Informatics
Marc-Andr矇 Kaufhold explores user expectations and design implications for the utilization of new media in crisis management and response. He develops a novel framework for information refinement, which integrates the event, organisational, societal, and technological perspectives of crises. Therefore, he reviews the state of the art on crisis informatics and empirically examines the use, potentials and barriers of both social media and mobile apps. Based on these insights, he designs and evaluates ICT concepts and artifacts with the aim to overcome the issues of information overload and quality in large-scale crises, concluding with practical and theoretical implications for technology adaptation and design.
Modern Information Technology and It Education
This book constitutes the refereed proceedings of the 12th International Conference on Modern Information Technology and IT Education, held in Moscow, Russia, in November 2017. The 30 papers presented were carefully reviewed and selected from 126 submissions. The papers are organized according to the following topics: IT-education: methodology, methodological support; e-learning and IT in education; educational resources and best practices of IT-education; research and development in the field of new IT and their applications; scientific software in education and science; school education in computer science and ICT; economic informatics.
Hands-On Data Analysis with Pandas - Second Edition
Get to grips with pandas by working with real datasets and master data discovery, data manipulation, data preparation, and handling data for analytical tasksKey FeaturesPerform efficient data analysis and manipulation tasks using pandas 1.xApply pandas to different real-world domains with the help of step-by-step examplesMake the most of pandas as an effective data exploration toolBook DescriptionExtracting valuable business insights is no longer a 'nice-to-have', but an essential skill for anyone who handles data in their enterprise. Hands-On Data Analysis with Pandas is here to help beginners and those who are migrating their skills into data science get up to speed in no time.This book will show you how to analyze your data, get started with machine learning, and work effectively with the Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn.Using real-world datasets, you will learn how to use the pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will learn how to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding chapters, you will explore some applications of anomaly detection, regression, clustering, and classification using scikit-learn to make predictions based on past data.This updated edition will equip you with the skills you need to use pandas 1.x to efficiently perform various data manipulation tasks, reliably reproduce analyses, and visualize your data for effective decision making - valuable knowledge that can be applied across multiple domains.What you will learnUnderstand how data analysts and scientists gather and analyze dataPerform data analysis and data wrangling using PythonCombine, group, and aggregate data from multiple sourcesCreate data visualizations with pandas, matplotlib, and seabornApply machine learning algorithms to identify patterns and make predictionsUse Python data science libraries to analyze real-world datasetsSolve common data representation and analysis problems using pandasBuild Python scripts, modules, and packages for reusable analysis codeWho this book is forThis book is for data science beginners, data analysts, and Python developers who want to explore each stage of data analysis and scientific computing using a wide range of datasets. Data scientists looking to implement pandas in their machine learning workflow will also find plenty of valuable know-how as they progress.You'll find it easier to follow along with this book if you have a working knowledge of the Python programming language, but a Python crash-course tutorial is provided in the code bundle for anyone who needs a refresher.Table of ContentsIntroduction to Data AnalysisWorking with Pandas DataFramesData Wrangling with PandasAggregating Pandas DataFramesVisualizing Data with Pandas and MatplotlibPlotting with Seaborn and Customization TechniquesFinancial Analysis - Bitcoin and the Stock MarketRule-Based Anomaly DetectionGetting Started with Machine Learning in PythonMaking Better Predictions - Optimizing ModelsMachine Learning Anomaly DetectionThe Road Ahead
Mastering Shiny
Master the Shiny web framework--and take your R skills to a whole new level. By letting you move beyond static reports, Shiny helps you create fully interactive web apps for data analyses. Users will be able to jump between datasets, explore different subsets or facets of the data, run models with parameter values of their choosing, customize visualizations, and much more. Hadley Wickham from RStudio shows data scientists, data analysts, statisticians, and scientific researchers with no knowledge of HTML, CSS, or JavaScript how to create rich web apps from R. This in-depth guide provides a learning path that you can follow with confidence, as you go from a Shiny beginner to an expert developer who can write large, complex apps that are maintainable and performant. Get started: Discover how the major pieces of a Shiny app fit together Put Shiny in action: Explore Shiny functionality with a focus on code samples, example apps, and useful techniques Master reactivity: Go deep into the theory and practice of reactive programming and examine reactive graph components Apply best practices: Examine useful techniques for making your Shiny apps work well in production
Hands-On Financial Trading with Python
Discover how to build and backtest algorithmic trading strategies with ZiplineKey Features: Get to grips with market data and stock analysis and visualize data to gain quality insightsFind out how to systematically approach quantitative research and strategy generation/backtesting in algorithmic tradingLearn how to navigate the different features in Python's data analysis librariesBook Description: Algorithmic trading helps you stay ahead of the markets by devising strategies in quantitative analysis to gain profits and cut losses.The book starts by introducing you to algorithmic trading and explaining why Python is the best platform for developing trading strategies. You'll then cover quantitative analysis using Python, and learn how to build algorithmic trading strategies with Zipline using various market data sources. Using Zipline as the backtesting library allows access to complimentary US historical daily market data until 2018. As you advance, you will gain an in-depth understanding of Python libraries such as NumPy and pandas for analyzing financial datasets, and explore Matplotlib, statsmodels, and scikit-learn libraries for advanced analytics. You'll also focus on time series forecasting, covering pmdarima and Facebook Prophet.By the end of this trading book, you will be able to build predictive trading signals, adopt basic and advanced algorithmic trading strategies, and perform portfolio optimization.What You Will Learn: Discover how quantitative analysis works by covering financial statistics and ARIMAUse core Python libraries to perform quantitative research and strategy development using real datasetsUnderstand how to access financial and economic data in PythonImplement effective data visualization with MatplotlibApply scientific computing and data visualization with popular Python librariesBuild and deploy backtesting algorithmic trading strategiesWho this book is for: This book is for data analysts and financial traders who want to explore how to design algorithmic trading strategies using Python's core libraries. If you are looking for a practical guide to backtesting algorithmic trading strategies and building your own strategies, then this book is for you. Beginner-level working knowledge of Python programming and statistics will be helpful.
Simulation Tools and Techniques
This two-volume set constitutes the refereed post-conference proceedings of the 12th International Conference on Simulation Tools and Techniques, SIMUTools 2020, held in Guiyang, China, in August 2020. Due to COVID-19 pandemic the conference was held virtually. The 125 revised full papers were carefully selected from 354 submissions. The papers focus on simulation methods, simulation techniques, simulation software, simulation performance, modeling formalisms, simulation verification and widely used frameworks.
Automated Machine Learning with AutoKeras
Create better and easy-to-use deep learning models with AutoKerasKey Features: Design and implement your own custom machine learning models using the features of AutoKerasLearn how to use AutoKeras for techniques such as classification, regression, and sentiment analysisGet familiar with advanced concepts as multi-modal, multi-task, and search space customizationBook Description: AutoKeras is an AutoML open-source software library that provides easy access to deep learning models. If you are looking to build deep learning model architectures and perform parameter tuning automatically using AutoKeras, then this book is for you.This book teaches you how to develop and use state-of-the-art AI algorithms in your projects. It begins with a high-level introduction to automated machine learning, explaining all the concepts required to get started with this machine learning approach. You will then learn how to use AutoKeras for image and text classification and regression. As you make progress, you'll discover how to use AutoKeras to perform sentiment analysis on documents. This book will also show you how to implement a custom model for topic classification with AutoKeras. Toward the end, you will explore advanced concepts of AutoKeras such as working with multi-modal data and multi-task, customizing the model with AutoModel, and visualizing experiment results using AutoKeras Extensions.By the end of this machine learning book, you will be able to confidently use AutoKeras to design your own custom machine learning models in your company.What You Will Learn: Set up a deep learning workstation with TensorFlow and AutoKerasAutomate a machine learning pipeline with AutoKerasCreate and implement image and text classifiers and regressors using AutoKerasUse AutoKeras to perform sentiment analysis of a text, classifying it as negative or positiveLeverage AutoKeras to classify documents by topicsMake the most of AutoKeras by using its most powerful extensionsWho this book is for: This book is for machine learning and deep learning enthusiasts who want to apply automated ML techniques to their projects. Prior basic knowledge of Python programming and machine learning is expected to get the most out of this book.
Becoming a Data Head
"Turn yourself into a Data Head. You'll become a more valuable employee and make your organization more successful."Thomas H. Davenport, Research Fellow, Author of Competing on Analytics, Big Data @ Work, and The AI Advantage You've heard the hype around data - now get the facts. In Becoming a Data Head: How to Think, Speak, and Understand Data Science, Statistics, and Machine Learning, award-winning data scientists Alex Gutman and Jordan Goldmeier pull back the curtain on data science and give you the language and tools necessary to talk and think critically about it. You'll learn how to: Think statistically and understand the role variation plays in your life and decision making Speak intelligently and ask the right questions about the statistics and results you encounter in the workplace Understand what's really going on with machine learning, text analytics, deep learning, and artificial intelligence Avoid common pitfalls when working with and interpreting data Becoming a Data Head is a complete guide for data science in the workplace: covering everything from the personalities you'll work with to the math behind the algorithms. The authors have spent years in data trenches and sought to create a fun, approachable, and eminently readable book. Anyone can become a Data Head--an active participant in data science, statistics, and machine learning. Whether you're a business professional, engineer, executive, or aspiring data scientist, this book is for you.
