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Automatic Retrieval With Locality Information Using SMART.

Chris Buckley, Gerard Salton, James Allan

Open publisher page 123 citations

Abstract

The Smart project at Cornell University, using a completely automatic approach for both routing and ad-hoc experiments, performed extremely well in the first Text Retrieval Conference. The basic ad-hoc approach uses local/global matching to achieve its results. A global match ensures that each retrieved document uses the same vocabulary as the query; a local match then attempts to guarantee some local part of the document (eg, a paragraph or sentence) focuses on the query algorithm is used for routing experiments

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What this paper is about

The Smart project at Cornell University, using a completely automatic approach for both routing and ad-hoc experiments, performed extremely well in the first Text Retrieval Conference. The basic ad-hoc approach uses local/global matching to achieve its results. A global match ensures that each retrieved document uses the same vocabulary as the query; a local match then attempts to guarantee some local part of the document (eg, a paragraph or sentence) focuses on the query algorithm is used for routing experiments

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OpenAlex reports 123 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

The Smart project at Cornell University, using a completely automatic approach for both routing and ad-hoc experiments, performed extremely well in the first Text Retrieval Conference. The basic ad-hoc approach uses local/global matching to achieve its results. A global match ensures that each retrieved document uses the same vocabulary as the query; a local match then attempts to guarantee some local part of the document (eg, a paragraph or sentence) focuses on the query algorithm is used for routing experiments

Key concepts: Paragraph, Computer science, Locality, Information retrieval, Vocabulary, Sentence, Matching (statistics), Routing (electronic design automation)

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