Abstract
A significant portion of web search queries directly refers to named entities. Search engines explore various ways to improve the user experience for such queries. We suggest augmenting search results with trivia facts about the searched entity. Trivia is widely played throughout the world, and was shown to increase users' engagement and retention. Most random facts are not suitable for the trivia section. There is skill (and art) to curating good trivia. In this paper, we formalize a notion of trivia-worthiness and propose an algorithm that automatically mines trivia facts from Wikipedia. We take advantage ofWikipedia's category structure, and rank an entity's categories by their triviaquality. Our algorithm is capable of finding interesting facts, such as Obama's Grammy or Elvis' stint as a tank gunner. In user studies, our algorithm captures the intuitive notion of "good trivia" 45% higher than prior work. Search-page tests show a 22% decrease in bounce rates and a 12% increase in dwell time, proving our facts hold users' attention.
Original language | English |
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Title of host publication | WSDM 2017 - Proceedings of the 10th ACM International Conference on Web Search and Data Mining |
Publisher | Association for Computing Machinery, Inc |
Pages | 345-354 |
Number of pages | 10 |
ISBN (Electronic) | 9781450346757 |
DOIs | |
State | Published - 2 Feb 2017 |
Event | 10th ACM International Conference on Web Search and Data Mining, WSDM 2017 - Cambridge, United Kingdom Duration: 6 Feb 2017 → 10 Feb 2017 |
Publication series
Name | WSDM 2017 - Proceedings of the 10th ACM International Conference on Web Search and Data Mining |
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Conference
Conference | 10th ACM International Conference on Web Search and Data Mining, WSDM 2017 |
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Country/Territory | United Kingdom |
City | Cambridge |
Period | 6/02/17 → 10/02/17 |
Bibliographical note
Publisher Copyright:© 2017 ACM.