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A Unified Framework for Recommending Diverse and Relevant Queries by Xiaofei Zhu; Jiafeng Guo; Xueqi Cheng; Pan Du; Hua-Wei Shen is a scholarly article available to read on EtoBox.

What is A Unified Framework for Recommending Diverse and Relevant Queries about?

Query recommendation has been considered as an effective way to help search users in their information seeking activities. Traditional approaches mainly focused on recommending alternative queries with close search intent to the original query. However, to only take relevance into account may generate redundant recommendations to users. It is better to provide diverse as well as relevant query recommendations, so that we can cover multiple potential search intents of users and minimize the risk that users will not be satisfied. Besides, previous query recommendation approaches mostly relied on measuring the relevance or similarity between queries in the Euclidean space. However, there is no convincing evidence that the query space is Euclidean. It is more natural and reasonable to assume that the query space is a manifold. In this paper, therefore, we aim to recommend diverse and relevant queries based on the intrinsic query manifold. We propose a unified model, named manifold ranking with stop points, for query recommendation. By turning ranked queries into stop points on the query manifold, our approach can generate query recommendations by simultaneously considering both diversi

Author

Xiaofei Zhu; Jiafeng Guo; Xueqi Cheng; Pan Du; Hua-Wei Shen

Publisher

ACM

Published

2011

Language

EN