On User Interactions with Query Auto-Completion

Bhaskar Mitra, Milad Shokouhi, Filip Radlinski, and Katja Hofmann

Abstract

Query Auto-Completion (QAC) is a popular feature of web search engines that aims to assist users to formulate queries faster and avoid spelling mistakes by presenting them with possible completions as soon as they start typing. However, despite the wide adoption of auto-completion in search systems, there is little published on how users interact with such services.

In this paper, we present the first large-scale study of user interactions with auto-completion based on query logs of Bing, a commercial search engine. Our results confirm that lower-ranked auto-completion suggestions receive substantially lower engagement than those ranked higher. We also observe that users are most likely to engage with auto-completion after typing about half of the query, and in particular at word boundaries. Interestingly, we also noticed that the likelihood of using auto-completion varies with the distance of query characters on the keyboard.

Overall, we believe that the results reported in our study provide valuable insights for understanding user engagement with auto-completion, and are likely to inform the design of more effective QAC systems.

Details

Publication typeProceedings
Published inProceedings of the ACM International Conference on Research and Development in Information Retrieval (SIGIR)
PublisherACM
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