文章基本信息

标题：Investigate the use of Anchor-Text and of Query-Document Similarity Scores to Predict the Performance of Search Engine
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作者：Abdulmohsen Almalawi ; Rayed AlGhamdi ; Adel Fahad 等
期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2017
卷号：8
期号：11
DOI：10.14569/IJACSA.2017.081140
出版社：Science and Information Society (SAI)
摘要：Query difficulty prediction aims to estimate, in advance, whether the answers returned by search engines in response to a query are likely to be useful. This paper proposes new predictors based upon the similarity between the query and answer documents, as calculated by the three different models. It examined the use of anchor text-based document surrogates, and how their similarity to queries can be used to estimate query difficulty. It evaluated the performance of the predictors based on 1) the correlation between the average precision (AP), 2) the precision at 10 (P@10) of the full text retrieved results, 3) a similarity score of anchor text, and 4) a similarity score of full-text, using the WT10g data collection of web data. Experimental evaluation of our research shows that five of our proposed predictors demonstrate reliable and consistent performance across a variety of different retrieval models.
关键词：Data mining; information retrieval; web search; query prediction