BE: a search engine for NLP research

Authors:
Michael J. Cafarella;Oren Etzioni
Affiliations:
University of Washington, Seattle, WA;University of Washington, Seattle, WA
Venue:
WAC '06 Proceedings of the 2nd International Workshop on Web as Corpus
Year:
2006

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Abstract

Many modern natural language-processing applications utilize search engines to locate large numbers of Web documents or to compute statistics over the Web corpus. Yet Web search engines are designed and optimized for simple human queries---they are not well suited to support such applications. As a result, these applications are forced to issue millions of successive queries resulting in unnecessary search engine load and in slow applications with limited scalability.