Abstract

Search satisfaction is defined as the fulfillment of a user’s information need. Characterizing and predicting the satisfaction of search engine users is vital for improving ranking models, increasing user retention rates, and growing market share. This article provides an overview of the research areas related to user satisfaction. First, we show that whenever users choose to defect from one search engine to another they do so mostly due to dissatisfaction with the search results. We also describe several search engine switching prediction methods, which could help search engines retain more users. Second, we discuss research on the difference between good and bad abandonment, which shows that in approximately 30% of all abandoned searches the users are in fact satisfied with the results. Third, we catalog techniques to determine queries and groups of queries that are underperforming in terms of user satisfaction. This can help improve search engines by developing specialized rankers for these query patterns. Fourth, we detail how task difficulty affects user behavior and how task difficulty can be predicted. Fifth, we characterize satisfaction and we compare major satisfaction prediction algorithms.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.