基于聚类分析的搜索引擎自动性能评价

传统的搜索引擎性能评价方法需要人工标注标准答案集,需花费大量的人力物力,并且评价结果依赖于人工标注的准确性,效率较低。该文基于聚类分析的思路,提出了一种搜索引擎性能评价指标和自动进行搜索引擎性能评价的方法,此方法能自动计算信息类查询的覆盖范围,并根据其覆盖范围对检索结果进行聚类,通过类间距和类内距等指标实现检索性能的自动评价。实验结果表明,基于聚类指标的评价方法与人工标注的评价方法的评价结果是相一致的。

Automatic Search Engine Performance Evaluation Based on Clustering Analysis

Traditional search engine evaluation methods need manual annotation of correct answers for a set of queries, which is costly and time comsuming. In this paper, we present an automatic search engine performance evaluation method based on clustering analysis. This method includes three stepsfirst, computing the coverage score of the query for information; second, clustering the search results by the coverage score; last, evaluating the retrieval performance using intra-cluster cohesion and inter-cluster separation. Experimental results show that the automatic method gets a similar evaluation result with traditional assessor-based ones.
Key wordsinformation retrieval; performance evaluation; clustering analysis