Selective cluster presentation on the search results page

Or Levi, Ido Guy, Fiana Raiber, Oren Kurland

Research output: Contribution to journalArticlepeer-review

9 Scopus citations


Web search engines present, for some queries, a cluster of results from the same specialized domain (“vertical”) on the search results page (SERP). We introduce a comprehensive analysis of the presentation of such clusters from seven different verticals based on the logs of a commercial Web search engine. This analysis reveals several unique characteristics—such as size, rank, and clicks—of result clusters from community question- and-answer websites. The study of properties of this result cluster—specifically as part of the SERP—has received little attention in previous work. Our analysis also motivates the pursuit of a long-standing challenge in ad hoc retrieval, namely, selective cluster retrieval. In our setting, the specific challenge is to select for presentation the documents most highly ranked either by a cluster-based approach (those in the top-retrieved cluster) or by a document-based approach. We address this classification task by representing queries with features based on those utilized for ranking the clusters, query-performance predictors, and properties of the document-clustering structure. Empirical evaluation performed with TREC data shows that our approach outperforms a recently proposed state-of-the-art cluster-based document-retrieval method as well as state-of-the-art document-retrieval methods that do not account for inter-document similarities.

Original languageEnglish
Article number28
JournalACM Transactions on Information Systems
Issue number3
StatePublished - 1 Jan 2018


  • Aggregated search
  • Cluster-based retrieval

ASJC Scopus subject areas

  • Information Systems
  • General Business, Management and Accounting
  • Computer Science Applications


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