The Web Of Data
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Reasoning Techniques For The Web Of Data
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Author : A. Hogan
language : en
Publisher: IOS Press
Release Date : 2014-04-09
Reasoning Techniques For The Web Of Data written by A. Hogan and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-04-09 with Computers categories.
Linked Data publishing has brought about a novel “Web of Data”: a wealth of diverse, interlinked, structured data published on the Web. These Linked Datasets are described using the Semantic Web standards and are openly available to all, produced by governments, businesses, communities and academia alike. However, the heterogeneity of such data – in terms of how resources are described and identified – poses major challenges to potential consumers. Herein, we examine use cases for pragmatic, lightweight reasoning techniques that leverage Web vocabularies (described in RDFS and OWL) to better integrate large scale, diverse, Linked Data corpora. We take a test corpus of 1.1 billion RDF statements collected from 4 million RDF Web documents and analyse the use of RDFS and OWL therein. We then detail and evaluate scalable and distributed techniques for applying rule-based materialisation to translate data between different vocabularies, and to resolve coreferent resources that talk about the same thing. We show how such techniques can be made robust in the face of noisy and often impudent Web data. We also examine a use case for incorporating a PagerRank-style algorithm to rank the trustworthiness of facts produced by reasoning, subsequently using those ranks to fix formal contradictions in the data. All of our methods are validated against our real world, large scale, open domain, Linked Data evaluation corpus.
Linked Data
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Author : Tom Heath
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2011-02-02
Linked Data written by Tom Heath and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-02-02 with Computers categories.
The World Wide Web has enabled the creation of a global information space comprising linked documents. As the Web becomes ever more enmeshed with our daily lives, there is a growing desire for direct access to raw data not currently available on the Web or bound up in hypertext documents. Linked Data provides a publishing paradigm in which not only documents, but also data, can be a first class citizen of the Web, thereby enabling the extension of the Web with a global data space based on open standards - the Web of Data. In this Synthesis lecture we provide readers with a detailed technical introduction to Linked Data. We begin by outlining the basic principles of Linked Data, including coverage of relevant aspects of Web architecture. The remainder of the text is based around two main themes - the publication and consumption of Linked Data. Drawing on a practical Linked Data scenario, we provide guidance and best practices on: architectural approaches to publishing Linked Data; choosing URIs and vocabularies to identify and describe resources; deciding what data to return in a description of a resource on the Web; methods and frameworks for automated linking of data sets; and testing and debugging approaches for Linked Data deployments. We give an overview of existing Linked Data applications and then examine the architectures that are used to consume Linked Data from the Web, alongside existing tools and frameworks that enable these. Readers can expect to gain a rich technical understanding of Linked Data fundamentals, as the basis for application development, research or further study. Table of Contents: List of Figures / Introduction / Principles of Linked Data / The Web of Data / Linked Data Design Considerations / Recipes for Publishing Linked Data / Consuming Linked Data / Summary and Outlook
The Web Of Data
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Author : Aidan Hogan
language : en
Publisher: Springer
Release Date : 2020-09-25
The Web Of Data written by Aidan Hogan and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-25 with Computers categories.
This book’s main goals are to bring together in a concise way all the methodologies, standards and recommendations related to Data, Queries, Links, Semantics, Validation and other issues concerning machine-readable data on the Web, to describe them in detail, to provide examples of their use, and to discuss how they contribute to – and how they have been used thus far on – the “Web of Data”. As the content of the Web becomes increasingly machine readable, increasingly complex tasks can be automated, yielding more and more powerful Web applications that are capable of discovering, cross-referencing, filtering, and organizing data from numerous websites in a matter of seconds. The book is divided into nine chapters, the first of which introduces the topic by discussing the shortcomings of the current Web and illustrating the need for a Web of Data. Next, “Web of Data” provides an overview of the fundamental concepts involved, and discusses some current use-cases on the Web where such concepts are already being employed. “Resource Description Framework (RDF)” describes the graph-structured data model proposed by the Semantic Web community as a common data model for the Web. The chapter on “RDF Schema (RDFS) and Semantics” presents a lightweight ontology language used to define an initial semantics for terms used in RDF graphs. In turn, the chapter “Web Ontology Language (OWL)” elaborates on a more expressive ontology language built upon RDFS that offers much more powerful ontological features. In “SPARQL Query Language” a language for querying and updating RDF graphs is described, with examples of the features it supports, supplemented by a detailed definition of its semantics. “Shape Constraints and Expressions (SHACL/ShEx)” introduces two languages for describing the expected structure of – and expressing constraints on – RDF graphs for the purposes of validation. “Linked Data” discusses the principles and best practices proposed by the Linked Data community for publishing interlinked (RDF) data on the Web, and how these techniques have been adopted. The final chapter highlights open problems and rounds out the coverage with a more general discussion on the future of the Web of Data. The book is intended for students, researchers and advanced practitioners interested in learning more about the Web of Data, and about closely related topics such as the Semantic Web, Knowledge Graphs, Linked Data, Graph Databases, Ontologies, etc. Offering a range of accessible examples and exercises, it can be used as a textbook for students and other newcomers to the field. It can also serve as a reference handbook for researchers and developers, as it offers up-to-date details on key standards (RDF, RDFS, OWL, SPARQL, SHACL, ShEx, RDB2RDF, LDP), along with formal definitions and references to further literature. The associated website webofdatabook.org offers a wealth of complementary material, including solutions to the exercises, slides for classes, raw data for examples, and a section for comments and questions.
Ranking For Web Data Search Using On The Fly Data Integration
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Author : Herzig, Daniel Markus
language : en
Publisher: KIT Scientific Publishing
Release Date : 2014-01-21
Ranking For Web Data Search Using On The Fly Data Integration written by Herzig, Daniel Markus and has been published by KIT Scientific Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-21 with Computers categories.
Ranking - the algorithmic decision on how relevant an information artifact is for a given information need and the sorting of artifacts by their concluded relevancy - is an integral part of every search engine. In this book we investigate how structured Web data can be leveraged for ranking with the goal to improve the effectiveness of search. We propose new solutions for ranking using on-the-fly data integration and experimentally analyze and evaluate them against the latest baselines.
Reasoning Web Reasoning And The Web In The Big Data Era
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Author : Manolis Koubarakis
language : en
Publisher: Springer
Release Date : 2014-09-03
Reasoning Web Reasoning And The Web In The Big Data Era written by Manolis Koubarakis and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-03 with Computers categories.
This volume contains the lecture notes of the 10th Reasoning Web Summer School 2014, held in Athens, Greece, in September 2014. In 2014, the lecture program of the Reasoning Web introduces students to recent advances in big data aspects of semantic web and linked data, and the fundamentals of reasoning techniques that can be used to tackle big data applications.
Engineering The Web In The Big Data Era
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Author : Philipp Cimiano
language : en
Publisher: Springer
Release Date : 2015-06-09
Engineering The Web In The Big Data Era written by Philipp Cimiano and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-09 with Computers categories.
This book constitutes the refereed proceedings of the 15th International Conference on Web Engineering, ICWE 2015, held in Rotterdam, The Netherlands, in June 2015. The 26 full research papers, 11 short papers, 7 industry papers, 11 demonstrations, 6 posters and 4 contributions to the PhD symposium presented were carefully reviewed and selected from 100 submissions. Moreover 2 tutorials are presented. The papers focus on eight tracks, namely Web application modeling and engineering; mobile Web applications; social Web applications; semantic Web applications; quality and accessibility aspects of Web applications; Web applications composition and mashups; Web user interfaces; security and privacy in Web applications.
Web Data Mining And The Development Of Knowledge Based Decision Support Systems
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Author : Sreedhar, G.
language : en
Publisher: IGI Global
Release Date : 2016-12-21
Web Data Mining And The Development Of Knowledge Based Decision Support Systems written by Sreedhar, G. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-12-21 with Computers categories.
Websites are a central part of today’s business world; however, with the vast amount of information that constantly changes and the frequency of required updates, this can come at a high cost to modern businesses. Web Data Mining and the Development of Knowledge-Based Decision Support Systems is a key reference source on decision support systems in view of end user accessibility and identifies methods for extraction and analysis of useful information from web documents. Featuring extensive coverage across a range of relevant perspectives and topics, such as semantic web, machine learning, and expert systems, this book is ideally designed for web developers, internet users, online application developers, researchers, and faculty.
Web Data Management Practices Emerging Techniques And Technologies
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Author : Vakali, Athena
language : en
Publisher: IGI Global
Release Date : 2006-09-30
Web Data Management Practices Emerging Techniques And Technologies written by Vakali, Athena and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-09-30 with Computers categories.
"This book provides an understanding of major issues, current practices and the main ideas in the field of Web data management, helping readers to identify current and emerging issues, as well as future trends. The most important aspects are discussed: Web data mining, content management on the Web, Web applications and Web services"--Provided by publisher.
Web Data Mining With Python
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Author : Dr. Ranjana Rajnish
language : en
Publisher: BPB Publications
Release Date : 2023-01-31
Web Data Mining With Python written by Dr. Ranjana Rajnish and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-31 with Computers categories.
Explore different web mining techniques to discover patterns, structures, and information from the web KEY FEATURES ● A complete overview of the basic and advanced concepts of Web mining. ● Work with easy-to-use open-source Python libraries for Web mining. ● Get familiar with the various beneficial areas and applications of Web mining. DESCRIPTION Data Science is the fastest growing job across the globe and is predicted to create 11.5 million jobs by 2026, so job seekers with this skill set have a lot of opportunities. One of the most sought areas in the field of Data Science is mining information from the web. If you are an aspiring Data Scientist looking to learn different Web mining techniques, then this book is for you. This book starts by covering the key concepts of Web mining and its taxonomy. It then explores the basics of Web scraping, its uses and components followed by topics like legal aspects related to scraping, data extraction and pre-processing, scraping dynamic websites, and CAPTCHA. The book also introduces you to the concept of Opinion mining and Web structure mining. Furthermore, it covers Web graph mining, Web information extraction, Web search and hyperlinks, Hyperlink Induced Topic Search (HITS) search, and partitioning algorithms that are used for Web mining. Towards the end, the book will teach you different mining techniques to discover interesting usage patterns from Web data. By the end of the book, you will master the art of data extraction using Python. WHAT YOU WILL LEARN ● Learn how to scrape data from any website with Python. ● Get familiar with the concepts of Opinion Mining and Sentiment Analysis. ● Use Web structure mining to discover structure information from the web. ● Learn how to collect and analyze social media data using Python. ● Use Web usage mining for predicting users' browsing behaviors. WHO THIS BOOK IS FOR The book is for anyone who wants to learn Web mining. Aspiring Data Scientists, Data Engineers, and Data Analysts who want to master Web mining will find this book very helpful. TABLE OF CONTENTS 1. Web Mining—An Introduction 2. Web Mining Taxonomy 3. Prominent Applications with Web Mining 4. Python Fundamentals 5. Web Scraping 6. Web Opinion Mining 7. Web Structure Mining 8. Social Network Analysis in Python 9. Web Usage Mining
Web Data Mining
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Author : Bing Liu
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-06-25
Web Data Mining written by Bing Liu and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-06-25 with Computers categories.
Liu has written a comprehensive text on Web mining, which consists of two parts. The first part covers the data mining and machine learning foundations, where all the essential concepts and algorithms of data mining and machine learning are presented. The second part covers the key topics of Web mining, where Web crawling, search, social network analysis, structured data extraction, information integration, opinion mining and sentiment analysis, Web usage mining, query log mining, computational advertising, and recommender systems are all treated both in breadth and in depth. His book thus brings all the related concepts and algorithms together to form an authoritative and coherent text. The book offers a rich blend of theory and practice. It is suitable for students, researchers and practitioners interested in Web mining and data mining both as a learning text and as a reference book. Professors can readily use it for classes on data mining, Web mining, and text mining. Additional teaching materials such as lecture slides, datasets, and implemented algorithms are available online.