- Series: Semantic Web and Beyond (Book 13)
- Hardcover: 220 pages
- Publisher: Springer; 2013 edition (August 1, 2012)
- Language: English
- ISBN-10: 1461418844
- ISBN-13: 978-1461418849
- Product Dimensions: 6.1 x 0.6 x 9.2 inches
- Shipping Weight: 1.1 pounds (View shipping rates and policies)
- Amazon Best Sellers Rank: #5,373,725 in Books (See Top 100 in Books)
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Social Semantics: The Search for Meaning on the Web (Semantic Web and Beyond) 2013th Edition
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From the book reviews:“Web practitioners working with search engines … or simply curious fellows who are interested not only in a practical description of things, but also like to think out of the box, will find the book valuable. … definitely recommend this book to all of my doctoral students, as it stimulates deep thinking on the web qua web as a subject matter. It should be of particular interest also to students and researchers in the new field of web science.” (M. Bielikova, Computing Reviews, October, 2014)
From the Back Cover
Statistical Semantics for the Semantic Web provides a unique introduction to identity and reference theories of the World Wide Web, through the academic lens of philosophy of language and data-driven statistical models. The Semantic Web is a natural evolution of the Web, and this book covers the URL-based Web architecture and Semantic Web in detail.Statistical Semantics for the Semantic Web discusses how the largest problem facing the Semantic Web is the problem of identity and reference, and how these are the results of a larger general theory of meaning. This book hypothesizes that statistical semantics can solve these problems, illustrated by case studies ranging from a pioneering study of tagging systems to using the Semantic Web to boost the results of commercial search engines. The substance matter of this book is rooted in the most difficult theoretical issues facing the Semantic Web today while having a robustly empirical side with an impact on industry.About this book: Presents case studies and experiments including the pioneering study of tagging systems.Covers performance of commercial search engines.Illustrates that the substance matter of this book has a robustly empirical side with impact on industry.This book targets practitioners working in the related fields of the semantic web, search engines, information retrieval, philosophers of language and more. Advanced-level students and researchers focusing on computer science will also find this book valuable as a secondary text or reference book.
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