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Search Personalization with Embeddings
- Publication Year :
- 2016
-
Abstract
- Recent research has shown that the performance of search personalization depends on the richness of user profiles which normally represent the user's topical interests. In this paper, we propose a new embedding approach to learning user profiles, where users are embedded on a topical interest space. We then directly utilize the user profiles for search personalization. Experiments on query logs from a major commercial web search engine demonstrate that our embedding approach improves the performance of the search engine and also achieves better search performance than other strong baselines.<br />Comment: In Proceedings of the 39th European Conference on Information Retrieval, ECIR 2017, to appear
Details
- Database :
- arXiv
- Publication Type :
- Report
- Accession number :
- edsarx.1612.03597
- Document Type :
- Working Paper
- Full Text :
- https://doi.org/10.1007/978-3-319-56608-5_54