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Comparing keyword search to semantic search: a case study in solving crossword puzzles using the Google™ API
Author(s) -
Goldschmidt David E.,
Krishnamoorthy Mukkai
Publication year - 2007
Publication title -
software: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.437
H-Index - 70
eISSN - 1097-024X
pISSN - 0038-0644
DOI - 10.1002/spe.840
Subject(s) - computer science , semantic search , information retrieval , social semantic web , semantic web , semantic web stack , world wide web , search engine , data web , semantic analytics , web search query , web search engine , web page
Keyword‐based search engines such as Google™ index Web pages for human consumption. Sophisticated as such engines have become, surveys indicate almost 25% of Web searchers are unable to find useful results in the first set of URLs returned ( Technology Review , March 2004). The lack of machine‐interpretable information on the Web limits software agents from matching human searches to desirable results. Tim Berners‐Lee, inventor of the Web, has architected the Semantic Web in which machine‐interpretable information provides an automated means to traversing the Web. A necessary cornerstone application is the search engine capable of bringing the Semantic Web together into a searchable landscape. We implemented a Semantic Web Search Engine ( SWSE ) that performs semantic search , providing predictable and accurate results to queries. To compare keyword search to semantic search, we constructed the Google CruciVerbalist ( GCV ), which solves crossword puzzles by reformulating clues into Google queries processed via the Google API. Candidate answers are extracted from query results. Integrating GCV with SWSE, we quantitatively show how semantic search improves upon keyword search. Mimicking the human brain's ability to create and traverse relationships between facts, our techniques enable Web applications to ‘think’ using semantic reasoning, opening the door to intelligent search applications that utilize the Semantic Web. Copyright © 2007 John Wiley & Sons, Ltd.