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To Suggest, or Not to Suggest for Queries with Diverse Intents: Optimizing Search Result Presentation

Published:08 February 2016Publication History

ABSTRACT

We propose a method of optimizing search result presentation for queries with diverse intents, by selectively presenting query suggestions for leading users to more relevant search results. The optimization is based on a probabilistic model of users who click on query suggestions in accordance with their intents, and modified versions of intent-aware evaluation metrics that take into account the co-occurrence between intents. Showing many query suggestions simply increases a chance to satisfy users with diverse intents in this model, while it in fact requires users to spend additional time for scanning and selecting suggestions, and may result in low satisfaction for some users. Therefore, we measured the loss of time caused by query suggestion presentation by conducting a user study in different settings, and included its negative effects in our optimization problem. Our experiments revealed that the optimization of search result presentation significantly improved that of a single ranked list, and was beneficial especially for patient users. Moreover, experimental results showed that our optimization was effective particularly when intents of a query often co-occur with a small subset of intents.

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    • Published in

      cover image ACM Conferences
      WSDM '16: Proceedings of the Ninth ACM International Conference on Web Search and Data Mining
      February 2016
      746 pages
      ISBN:9781450337168
      DOI:10.1145/2835776

      Copyright © 2016 ACM

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      Publication History

      • Published: 8 February 2016

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      WSDM '16 Paper Acceptance Rate67of368submissions,18%Overall Acceptance Rate498of2,863submissions,17%

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