Abstract
We consider the problem of ranking relevant verticals for a given mobile search query so as to satisfy the average user. To this end, we utilise real mobile search click logs, and apply a graph contruction algorithm proposed by Agrawal et al. who tackled the problem of automatically assigning relevance labels to URLs for general web search. While Agrawal et al. ordered URLs based on pairwise preferences and then partitioned the ordered URL list to determine absolute relevance grades, our objective is to rank a given set of verticals for a given query, to help search engine companies select which verticals to include in a search engine result page for a small smartphone screen. We show that "Click > Skip Other" preference rules consistently outperform more conservative rules such as "Click > Skip Previous" and that our best graph-based vertical ranking methods substantially and statistically significantly outperform a competitive baseline that ranks verticals based on click counts.
Original language | English |
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Title of host publication | ICTIR 2017 - Proceedings of the 2017 ACM SIGIR International Conference on the Theory of Information Retrieval |
Publisher | Association for Computing Machinery, Inc |
Pages | 225-228 |
Number of pages | 4 |
ISBN (Electronic) | 9781450344906 |
DOIs | |
Publication status | Published - 2017 Oct 1 |
Event | 7th ACM SIGIR International Conference on the Theory of Information Retrieval, ICTIR 2017 - Amsterdam, Netherlands Duration: 2017 Oct 1 → 2017 Oct 4 |
Other
Other | 7th ACM SIGIR International Conference on the Theory of Information Retrieval, ICTIR 2017 |
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Country | Netherlands |
City | Amsterdam |
Period | 17/10/1 → 17/10/4 |
Keywords
- Click logs
- Mobile search
- Pairwise preferences
- Vertical ranking
ASJC Scopus subject areas
- Information Systems
- Computer Science (miscellaneous)