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Books > Computing & IT > Applications of computing > Artificial intelligence
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Semantic Search over the Web (Paperback, 2012 ed.)
Loot Price: R1,562
Discovery Miles 15 620
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Semantic Search over the Web (Paperback, 2012 ed.)
Series: Data-Centric Systems and Applications
Expected to ship within 10 - 15 working days
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The Web has become the world's largest database, with search being
the main tool that allows organizations and individuals to exploit
its huge amount of information. Search on the Web has been
traditionally based on textual and structural similarities,
ignoring to a large degree the semantic dimension, i.e.,
understanding the meaning of the query and of the document content.
Combining search and semantics gives birth to the idea of semantic
search. Traditional search engines have already advertised some
semantic dimensions. Some of them, for instance, can enhance their
generated result sets with documents that are semantically related
to the query terms even though they may not include these terms.
Nevertheless, the exploitation of the semantic search has not yet
reached its full potential. In this book, Roberto De Virgilio,
Francesco Guerra and Yannis Velegrakis present an extensive
overview of the work done in Semantic Search and other related
areas. They explore different technologies and solutions in depth,
making their collection a valuable and stimulating reading for both
academic and industrial researchers. The book is divided into three
parts. The first introduces the readers to the basic notions of the
Web of Data. It describes the different kinds of data that exist,
their topology, and their storing and indexing techniques. The
second part is dedicated to Web Search. It presents different types
of search, like the exploratory or the path-oriented, alongside
methods for their efficient and effective implementation. Other
related topics included in this part are the use of uncertainty in
query answering, the exploitation of ontologies, and the use of
semantics in mashup design and operation. The focus of the third
part is on linked data, and more specifically, on applying ideas
originating in recommender systems on linked data management, and
on techniques for the efficiently querying answering on linked
data.
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