在非常大的文本集合上进行临时检索的术语接近度评分

Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval Pub Date : 2006-08-06 DOI:10.1145/1148170.1148285

Stefan Büttcher, C. Clarke, Brad Lushman

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引用次数: 183

摘要

我们建议将术语接近度评分整合到霍加狓BM25中。与纯BM25相比，我们的检索方法的相对检索效率因收集而异。我们对我们的方法进行了实验评估，并显示了随着底层文本集合的大小增加，在BM25上获得的收益。我们还表明，对于有词源的查询，术语接近度评分的影响大于无词源的查询。

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Term proximity scoring for ad-hoc retrieval on very large text collections

We propose an integration of term proximity scoring into Okapi BM25. The relative retrieval effectiveness of our retrieval method, compared to pure BM25, varies from collection to collection.We present an experimental evaluation of our method and show that the gains achieved over BM25 as the size of the underlying text collection increases. We also show that for stemmed queries the impact of term proximity scoring is larger than for unstemmed queries.

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Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval

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