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

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...

• Type: Journal
• Year: 2016
• Where: WSDM
• Authors: Makoto P. Kato, Katsumi Tanaka
• Keywords: Data Mining, WSDM 2016