Learning to evaluate and recommend query in restaurant search systems

被引:0
作者
Xian Chen
Hyoseop Shin
Hyang-won Lee
机构
[1] Konkuk University,Department of Internet and Multimedia Engineering
来源
Information Systems and e-Business Management | 2017年 / 15卷
关键词
Query recommender system; Quality of queries; Query suggestion; Learning to measure; Learning to rank;
D O I
暂无
中图分类号
学科分类号
摘要
Users tend to use their own terms to search items in structured search systems such as restaurant searches (e.g. Yelp), but due to users’ lack of understanding on internal vocabulary and structures, they often fail to adequately search, which leads to unsatisfying search results. In this case, search systems should assist users to use different terms for better search results. To address this issue, we develop a scheme to generate suggested queries, given a user query. We propose a scheme to evaluate queries (i.e. user queries and suggested queries) based on two measures: (1) if the query will return a sufficient number of search results, (2) if the query will return search results of high quality. Furthermore, we present a learning model to choose among alternative candidate queries against a user query. Then we provide learning to rank suggested queries and return to users. Our experiments show the proposed method provides feasible and scalable solution for query evaluation and recommendation of vertical search systems.
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页码:51 / 68
页数:17
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