Discovering meaning on the go in large heterogenous data
Artificial Intelligence Review
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Social Semantics: The Search for Meaning on the Webprovides 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. It has a robust empirical side which has an impact on industry. Social Semantics: The Search for Meaning on the 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. Social Semantics: The Search for Meaning on the Webtargets 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.