A Keyword Based Prototype for Web Search Result Diversification
Guli Lin, Hong Peng, Qianli Ma, Jia Wei, Jiang-Wei Qin · 2012
In Web search scenario, users often submit short query terms to search engines, ex-pecting to find their desired information in top ranked results. But their queries are so ambiguous that their actual information needs are often unspecified. To satisfy the dif-ferent information needs, an effective approach is to diversify the top results retrieved for the query. In this paper, we reduce the diversification problem into optimizing the maxi-mum coverage of information facets related to the query, and introduce KED, a novel keyword based prototype for Web search result diversification that provides a diverse ranking by selecting documents to cover keywords which belong to different facets un-derlying the retrieved documents. We evaluated the effectiveness of KED using two pub-lic test collections with different kinds of documents. The experiment results show that KED can stably outperform other existing implicit diversification approaches in promot-ing diversity of top ranked results. Moreover, we show that its effectiveness can be fur-ther improved by using high quality keywords.