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Discovery of Similarity Computations of Search Engines

机译:搜索引擎相似度计算的发现

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摘要

Two typical situations in which it is of practical interest to determine the similarities of text documents to a query due to a search engine are; (1) a global search engine, con-structed on top of a group of local search engines, wishes to retrieve the set of local documents globally most similar to a given query; and (2) an organization wants to compare the retrieval performance of search engines. The dot-product function is a widely used similarity function. For a search engine using such a function, we can determine its similarity computations if how the search engine sets the weights of terms is known, which is usually not the case. In this paper, techniques are presented to discover certain mathematical expressions of these formulas and the values of embedded constants when the dot-product similarity function is used. Preliminary results from experiments on the WebCrawler search engine are given to illustrate our techniques.~1
机译:确定文本文档与由于搜索引擎而引起的查询的相似性具有实际意义的两种典型情况是: (1)构造在一组本地搜索引擎之上的全局搜索引擎希望全局检索与给定查询最相似的一组本地文档; (2)一个组织想要比较搜索引擎的检索性能。点积函数是广泛使用的相似性函数。对于使用这种功能的搜索引擎,如果搜索引擎如何设置术语权重,我们可以确定其相似度计算,通常不是这种情况。在本文中,提出了使用点积相似函数来发现这些公式的某些数学表达式以及嵌入常数的值的技术。给出了WebCrawler搜索引擎上实验的初步结果,以说明我们的技术。〜1

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