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Constructing Web search queries from the user's information need expressed in a natural language

机译:根据以自然语言表达的用户信息需求构造Web搜索查询

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This paper focuses on improving the quality of information retrieval on the Web through the use of long queries. Long queries allow use of natural language and provide for a more complete description of the user's information need. We propose and analyze several novel algorithms dealing with long query information retrieval on the Web. These algorithms include selecting of search terms, constructing multiple query formulations, merging and ranking search results. We developed a meta-search engine, incorporating the proposed algorithms, and conducted a series of experiments to evaluate the performance of various algorithms. We also compared search results of the new engine with the results of popular search engines on the Web. These experiments clearly demonstrate that using long queries in the Web environment is practical and can substantially improve the quality of information retrieval.
机译:本文着重于通过使用长查询来提高Web上信息检索的质量。长查询允许使用自然语言并提供对用户信息需求的更完整描述。我们提出并分析了几种新颖的算法,用于处理Web上的长查询信息检索。这些算法包括选择搜索词,构建多个查询表述,合并搜索结果并对其进行排名。我们开发了包含建议算法的元搜索引擎,并进行了一系列实验以评估各种算法的性能。我们还将新引擎的搜索结果与网络上流行的搜索引擎的结果进行了比较。这些实验清楚地表明,在Web环境中使用长查询是切实可行的,并且可以大大提高信息检索的质量。

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