{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/18504"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/18504","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Enabling Vertical Search Over Wikipedia","abstract":"The massive amount of information on the Web has led to the proliferation of vertical search engines, which are specialized for specific domains. Such engines can offer superior results through gathering and utilizing domain-specific information. In this thesis, we explore the idea of applying similar techniques to Wikipedia. We construct a conceptual model of vertical search and explain why Wikipedia is especially suitable for this form of search. We go on to analyze the difficulties of making full use of Wikipedia's advantages, and offer possible solutions. These solutions were tested through implementation of simple search scenarios across two distinct database architectures. Finally, we compare the performance and ease of implementation of the two architectures, consider the quality of results obtained from our searches, and offer suggestions for future work.","abstract_html":"The massive amount of information on the Web has led to the proliferation of vertical search engines, which are specialized for specific domains. Such engines can offer superior results through gathering and utilizing domain-specific information. In this thesis, we explore the idea of applying similar techniques to Wikipedia. We construct a conceptual model of vertical search and explain why Wikipedia is especially suitable for this form of search. We go on to analyze the difficulties of making full use of Wikipedia's advantages, and offer possible solutions. These solutions were tested through implementation of simple search scenarios across two distinct database architectures. 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