Exploiting Semantic Web Knowledge Graphs in Data Mining

Exploiting Semantic Web Knowledge Graphs in Data Mining

Author: P. Ristoski

Publisher: IOS Press

Published: 2019-06-28

Total Pages: 246

ISBN-13: 1614999813

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Data Mining and Knowledge Discovery in Databases (KDD) is a research field concerned with deriving higher-level insights from data. The tasks performed in this field are knowledge intensive and can benefit from additional knowledge from various sources, so many approaches have been proposed that combine Semantic Web data with the data mining and knowledge discovery process. This book, Exploiting Semantic Web Knowledge Graphs in Data Mining, aims to show that Semantic Web knowledge graphs are useful for generating valuable data mining features that can be used in various data mining tasks. In Part I, Mining Semantic Web Knowledge Graphs, the author evaluates unsupervised feature generation strategies from types and relations in knowledge graphs used in different data mining tasks such as classification, regression, and outlier detection. Part II, Semantic Web Knowledge Graphs Embeddings, proposes an approach that circumvents the shortcomings introduced with the approaches in Part I, developing an approach that is able to embed complete Semantic Web knowledge graphs in a low dimensional feature space where each entity and relation in the knowledge graph is represented as a numerical vector. Finally, Part III, Applications of Semantic Web Knowledge Graphs, describes a list of applications that exploit Semantic Web knowledge graphs like classification and regression, showing that the approaches developed in Part I and Part II can be used in applications in various domains. The book will be of interest to all those working in the field of data mining and KDD.


Book Synopsis Exploiting Semantic Web Knowledge Graphs in Data Mining by : P. Ristoski

Download or read book Exploiting Semantic Web Knowledge Graphs in Data Mining written by P. Ristoski and published by IOS Press. This book was released on 2019-06-28 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining and Knowledge Discovery in Databases (KDD) is a research field concerned with deriving higher-level insights from data. The tasks performed in this field are knowledge intensive and can benefit from additional knowledge from various sources, so many approaches have been proposed that combine Semantic Web data with the data mining and knowledge discovery process. This book, Exploiting Semantic Web Knowledge Graphs in Data Mining, aims to show that Semantic Web knowledge graphs are useful for generating valuable data mining features that can be used in various data mining tasks. In Part I, Mining Semantic Web Knowledge Graphs, the author evaluates unsupervised feature generation strategies from types and relations in knowledge graphs used in different data mining tasks such as classification, regression, and outlier detection. Part II, Semantic Web Knowledge Graphs Embeddings, proposes an approach that circumvents the shortcomings introduced with the approaches in Part I, developing an approach that is able to embed complete Semantic Web knowledge graphs in a low dimensional feature space where each entity and relation in the knowledge graph is represented as a numerical vector. Finally, Part III, Applications of Semantic Web Knowledge Graphs, describes a list of applications that exploit Semantic Web knowledge graphs like classification and regression, showing that the approaches developed in Part I and Part II can be used in applications in various domains. The book will be of interest to all those working in the field of data mining and KDD.

Social Semantic Web Mining

Social Semantic Web Mining

Author: Tope Omitola

Publisher: Morgan & Claypool Publishers

Published: 2015-01-01

Total Pages: 156

ISBN-13: 1627053999

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The past ten years have seen a rapid growth in the numbers of people signing up to use Web-based social networks (hundreds of millions of new members are now joining the main services each year) with a large amount of content being shared on these networks (tens of billions of content items are shared each month). With this growth in usage and data being generated, there are many opportunities to discover the knowledge that is often inherent but somewhat hidden in these networks. Web mining techniques are being used to derive this hidden knowledge. In addition, the Semantic Web, including the Linked Data initiative to connect previously disconnected datasets, is making it possible to connect data from across various social spaces through common representations and agreed upon terms for people, content items, etc. In this book, we detail some current research being carried out to semantically represent the implicit and explicit structures on the Social Web, along with the techniques being used to elicit relevant knowledge from these structures, and we present the mechanisms that can be used to intelligently mesh these semantic representations with intelligent knowledge discovery processes. We begin this book with an overview of the origins of the Web, and then show how web intelligence can be derived from a combination of web and Social Web mining. We give an overview of the Social and Semantic Webs, followed by a description of the combined Social Semantic Web (along with some of the possibilities it affords), and the various semantic representation formats for the data created in social networks and on social media sites. Provenance and provenance mining is an important aspect here, especially when data is combined from multiple services. We will expand on the subject of provenance and especially its importance in relation to social data. We will describe extensions to social semantic vocabularies specifically designed for community mining purposes (SIOCM). In the last three chapters, we describe how the combination of web intelligence and social semantic data can be used to derive knowledge from the Social Web, starting at the community level (macro), and then moving through group mining (meso) to user profile mining (micro). Table of Contents: Acknowledgments / Grant Aid / Introduction and the Web / Web Mining / The Social Web / The Semantic Web / The Social Semantic Web / Social Semantic Web Mining / Social Semantic Web Mining of Communities / Social Semantic Web Mining of Groups / Social Semantic Web Mining of Users / Conclusions / Bibliography / Authors' Biographies


Book Synopsis Social Semantic Web Mining by : Tope Omitola

Download or read book Social Semantic Web Mining written by Tope Omitola and published by Morgan & Claypool Publishers. This book was released on 2015-01-01 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt: The past ten years have seen a rapid growth in the numbers of people signing up to use Web-based social networks (hundreds of millions of new members are now joining the main services each year) with a large amount of content being shared on these networks (tens of billions of content items are shared each month). With this growth in usage and data being generated, there are many opportunities to discover the knowledge that is often inherent but somewhat hidden in these networks. Web mining techniques are being used to derive this hidden knowledge. In addition, the Semantic Web, including the Linked Data initiative to connect previously disconnected datasets, is making it possible to connect data from across various social spaces through common representations and agreed upon terms for people, content items, etc. In this book, we detail some current research being carried out to semantically represent the implicit and explicit structures on the Social Web, along with the techniques being used to elicit relevant knowledge from these structures, and we present the mechanisms that can be used to intelligently mesh these semantic representations with intelligent knowledge discovery processes. We begin this book with an overview of the origins of the Web, and then show how web intelligence can be derived from a combination of web and Social Web mining. We give an overview of the Social and Semantic Webs, followed by a description of the combined Social Semantic Web (along with some of the possibilities it affords), and the various semantic representation formats for the data created in social networks and on social media sites. Provenance and provenance mining is an important aspect here, especially when data is combined from multiple services. We will expand on the subject of provenance and especially its importance in relation to social data. We will describe extensions to social semantic vocabularies specifically designed for community mining purposes (SIOCM). In the last three chapters, we describe how the combination of web intelligence and social semantic data can be used to derive knowledge from the Social Web, starting at the community level (macro), and then moving through group mining (meso) to user profile mining (micro). Table of Contents: Acknowledgments / Grant Aid / Introduction and the Web / Web Mining / The Social Web / The Semantic Web / The Social Semantic Web / Social Semantic Web Mining / Social Semantic Web Mining of Communities / Social Semantic Web Mining of Groups / Social Semantic Web Mining of Users / Conclusions / Bibliography / Authors' Biographies

Web Mining

Web Mining

Author: Bettina Berendt

Publisher:

Published: 2014-01-15

Total Pages: 218

ISBN-13: 9783662185919

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Book Synopsis Web Mining by : Bettina Berendt

Download or read book Web Mining written by Bettina Berendt and published by . This book was released on 2014-01-15 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Semantic Data Mining

Semantic Data Mining

Author: A. Ławrynowicz

Publisher: IOS Press

Published: 2017-04-18

Total Pages: 210

ISBN-13: 1614997462

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Ontologies are now increasingly used to integrate, and organize data and knowledge, particularly in data and knowledge-intensive applications in both research and industry. The book is devoted to semantic data mining – a data mining approach where domain ontologies are used as background knowledge, and where the new challenge is to mine knowledge encoded in domain ontologies and knowledge graphs, rather than only purely empirical data. The introductory chapters of the book provide theoretical foundations of both data mining and ontology representation. Taking a unified perspective, the book then covers several methods for semantic data mining, addressing tasks such as pattern mining, classification and similarity-based approaches. It attempts to provide state-of-the-art answers to specific challenges and peculiarities of data mining with use of ontologies, in particular: How to deal with incompleteness of knowledge and the so-called Open World Assumption? What is a truly “semantic” similarity measure? The book contains several chapters with examples of applications of semantic data mining. The examples start from a scenario with moderate use of lightweight ontologies for knowledge graph enrichment and end with a full-fledged scenario of an intelligent knowledge discovery assistant using complex domain ontologies for meta-mining, i.e., an ontology-based meta-learning approach to full data mining processes. The book is intended for researchers in the fields of semantic technologies, knowledge engineering, data science, and data mining, and developers of knowledge-based systems and applications.


Book Synopsis Semantic Data Mining by : A. Ławrynowicz

Download or read book Semantic Data Mining written by A. Ławrynowicz and published by IOS Press. This book was released on 2017-04-18 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ontologies are now increasingly used to integrate, and organize data and knowledge, particularly in data and knowledge-intensive applications in both research and industry. The book is devoted to semantic data mining – a data mining approach where domain ontologies are used as background knowledge, and where the new challenge is to mine knowledge encoded in domain ontologies and knowledge graphs, rather than only purely empirical data. The introductory chapters of the book provide theoretical foundations of both data mining and ontology representation. Taking a unified perspective, the book then covers several methods for semantic data mining, addressing tasks such as pattern mining, classification and similarity-based approaches. It attempts to provide state-of-the-art answers to specific challenges and peculiarities of data mining with use of ontologies, in particular: How to deal with incompleteness of knowledge and the so-called Open World Assumption? What is a truly “semantic” similarity measure? The book contains several chapters with examples of applications of semantic data mining. The examples start from a scenario with moderate use of lightweight ontologies for knowledge graph enrichment and end with a full-fledged scenario of an intelligent knowledge discovery assistant using complex domain ontologies for meta-mining, i.e., an ontology-based meta-learning approach to full data mining processes. The book is intended for researchers in the fields of semantic technologies, knowledge engineering, data science, and data mining, and developers of knowledge-based systems and applications.

Web Mining: From Web to Semantic Web

Web Mining: From Web to Semantic Web

Author: Bettina Berendt

Publisher: Springer Science & Business Media

Published: 2004-09-23

Total Pages: 210

ISBN-13: 3540232583

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This book originates from the first European Web Mining Forum, EWMF 2003, held in Cavtat-Dubrovnik, Croatia, in September 2003 in association with ECML/PKDD 2003. The Web Mining Forum initiative is motivated by the insight that knowledge discovery on the Web, from the viewpoint of hyperarchive analysis, and, from the viewpoint of interaction among persons and institutions, are complementary, both for the conventional Web and for the Semantic Web. This book presents an introductory roadmap paper, four invited papers and six workshop papers, which were carefully selected during two rounds of reviewing and improvement. Among the topics addressed are Web usage mining, Web mining for the addition of semantics, semantically enhanced Web filtering, ontologies, wrapper induction, Web personalization, user profiling, user session evaluation, and evolution of Web usage patterns.


Book Synopsis Web Mining: From Web to Semantic Web by : Bettina Berendt

Download or read book Web Mining: From Web to Semantic Web written by Bettina Berendt and published by Springer Science & Business Media. This book was released on 2004-09-23 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book originates from the first European Web Mining Forum, EWMF 2003, held in Cavtat-Dubrovnik, Croatia, in September 2003 in association with ECML/PKDD 2003. The Web Mining Forum initiative is motivated by the insight that knowledge discovery on the Web, from the viewpoint of hyperarchive analysis, and, from the viewpoint of interaction among persons and institutions, are complementary, both for the conventional Web and for the Semantic Web. This book presents an introductory roadmap paper, four invited papers and six workshop papers, which were carefully selected during two rounds of reviewing and improvement. Among the topics addressed are Web usage mining, Web mining for the addition of semantics, semantically enhanced Web filtering, ontologies, wrapper induction, Web personalization, user profiling, user session evaluation, and evolution of Web usage patterns.

Semantic Data Mining

Semantic Data Mining

Author: Agnieszka Ławrynowicz

Publisher:

Published: 2017

Total Pages: 194

ISBN-13: 9783898387248

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"Ontologies are now increasingly used to integrate, and organize data and knowledge, particularly in data and knowledge-intensive applications in both research and industry. The book is devoted to semantic data mining--a data mining approach where domain ontologies are used as background knowledge, and where the new challenge is to mine knowledge encoded in domain ontologies and knowledge graphs, rather than only purely empirical data."--page [4] of cover.


Book Synopsis Semantic Data Mining by : Agnieszka Ławrynowicz

Download or read book Semantic Data Mining written by Agnieszka Ławrynowicz and published by . This book was released on 2017 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Ontologies are now increasingly used to integrate, and organize data and knowledge, particularly in data and knowledge-intensive applications in both research and industry. The book is devoted to semantic data mining--a data mining approach where domain ontologies are used as background knowledge, and where the new challenge is to mine knowledge encoded in domain ontologies and knowledge graphs, rather than only purely empirical data."--page [4] of cover.

Advancing Information Management through Semantic Web Concepts and Ontologies

Advancing Information Management through Semantic Web Concepts and Ontologies

Author: Ordóñez de Pablos, Patricia

Publisher: IGI Global

Published: 2012-11-30

Total Pages: 434

ISBN-13: 1466624957

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"This book provides an analysis and introduction on the concept of combining the areas of semantic web and web mining, emphasizing semantics in technologies, reasoning, content searching and social media"--Provided by publisher.


Book Synopsis Advancing Information Management through Semantic Web Concepts and Ontologies by : Ordóñez de Pablos, Patricia

Download or read book Advancing Information Management through Semantic Web Concepts and Ontologies written by Ordóñez de Pablos, Patricia and published by IGI Global. This book was released on 2012-11-30 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book provides an analysis and introduction on the concept of combining the areas of semantic web and web mining, emphasizing semantics in technologies, reasoning, content searching and social media"--Provided by publisher.

Semantic Web and Web Science

Semantic Web and Web Science

Author: Juanzi Li

Publisher: Springer Science & Business Media

Published: 2013-06-13

Total Pages: 395

ISBN-13: 1461468809

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The book will focus on exploiting state of the art research in semantic web and web science. The rapidly evolving world-wide-web has led to revolutionary changes in the whole of society. The research and development of the semantic web covers a number of global standards of the web and cutting edge technologies, such as: linked data, social semantic web, semantic web search, smart data integration, semantic web mining and web scale computing. These proceedings are from the 6th Chinese Semantics Web Symposium.


Book Synopsis Semantic Web and Web Science by : Juanzi Li

Download or read book Semantic Web and Web Science written by Juanzi Li and published by Springer Science & Business Media. This book was released on 2013-06-13 with total page 395 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book will focus on exploiting state of the art research in semantic web and web science. The rapidly evolving world-wide-web has led to revolutionary changes in the whole of society. The research and development of the semantic web covers a number of global standards of the web and cutting edge technologies, such as: linked data, social semantic web, semantic web search, smart data integration, semantic web mining and web scale computing. These proceedings are from the 6th Chinese Semantics Web Symposium.

Applied Semantic Web Technologies

Applied Semantic Web Technologies

Author: Vijayan Sugumaran

Publisher: CRC Press

Published: 2011-08-12

Total Pages: 476

ISBN-13: 1439801576

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The rapid advancement of semantic web technologies, along with the fact that they are at various levels of maturity, has left many practitioners confused about the current state of these technologies. Focusing on the most mature technologies, Applied Semantic Web Technologies integrates theory with case studies to illustrate the history, current st


Book Synopsis Applied Semantic Web Technologies by : Vijayan Sugumaran

Download or read book Applied Semantic Web Technologies written by Vijayan Sugumaran and published by CRC Press. This book was released on 2011-08-12 with total page 476 pages. Available in PDF, EPUB and Kindle. Book excerpt: The rapid advancement of semantic web technologies, along with the fact that they are at various levels of maturity, has left many practitioners confused about the current state of these technologies. Focusing on the most mature technologies, Applied Semantic Web Technologies integrates theory with case studies to illustrate the history, current st

Web 2.0 & Semantic Web

Web 2.0 & Semantic Web

Author: Vladan Devedžic

Publisher: Springer Science & Business Media

Published: 2010-01-08

Total Pages: 206

ISBN-13: 1441912193

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According to the W3C Semantic Web Activity [1]: The Semantic Web provides a common framework that allows data to be shared and reused across appli- tion, enterprise, and community boundaries. This statement clearly explains that the Semantic Web is about data sharing. Currently, the Web uses hyperlinks to connect Web pages. The Semantic Web goes beyond that and focuses on data and envisions the creation of the web of data. On the Semantic Web, anyone can say anything about any resource on the Web. This is fully based on the concept of semantic - notations, where each resource on the Web can have an assigned meaning. This is done through the use of ontologies as a formal and explicit representation of domain concepts and their relationships [2]. Ontologies are formally based on description logics. This enables agents and applications to reason over the data when searching the Web, which has not previously been possible. Web 2. 0 has gradually evolved from letting the Web users play a more active role. Unlike the initial version of the Web, where the users mainly “consumed” content, users are now offered easy-to-use services for content production and publication. Mashups, blogs, wikis, feeds, interface remixes, and social networking/tagging s- tems are examples of these well-known services. The success and wide adoption of Web 2. 0 was in its reliance on social interactions as an inevitable characteristic of the use and life of the Web. In particular, Web 2.


Book Synopsis Web 2.0 & Semantic Web by : Vladan Devedžic

Download or read book Web 2.0 & Semantic Web written by Vladan Devedžic and published by Springer Science & Business Media. This book was released on 2010-01-08 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt: According to the W3C Semantic Web Activity [1]: The Semantic Web provides a common framework that allows data to be shared and reused across appli- tion, enterprise, and community boundaries. This statement clearly explains that the Semantic Web is about data sharing. Currently, the Web uses hyperlinks to connect Web pages. The Semantic Web goes beyond that and focuses on data and envisions the creation of the web of data. On the Semantic Web, anyone can say anything about any resource on the Web. This is fully based on the concept of semantic - notations, where each resource on the Web can have an assigned meaning. This is done through the use of ontologies as a formal and explicit representation of domain concepts and their relationships [2]. Ontologies are formally based on description logics. This enables agents and applications to reason over the data when searching the Web, which has not previously been possible. Web 2. 0 has gradually evolved from letting the Web users play a more active role. Unlike the initial version of the Web, where the users mainly “consumed” content, users are now offered easy-to-use services for content production and publication. Mashups, blogs, wikis, feeds, interface remixes, and social networking/tagging s- tems are examples of these well-known services. The success and wide adoption of Web 2. 0 was in its reliance on social interactions as an inevitable characteristic of the use and life of the Web. In particular, Web 2.