Query suggestion using hitting time

By Qiaozhu Mei, Dengyong Zhou, Kenneth Ward Church. International Conference on Information and Knowledge Management, 2008

371 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Identifying Web Search Query Reformulation using Concept based Matching (2013, methodology): “Mei et al. (2008) used random walks over a bipartite graph of queries and URLs to ﬁnd query reﬁne-ments.”
Learning to personalize trending image search suggestion (2014, background): “The second branch is based on document-click relationship [6, 23].”
Semantic Matching in Search (2014, neutral): “[133].”
A survey of types of text noise and techniques to handle noisy text (2009, background): “Authors have proposed a technique to rank alternate queries based on hitting time on a large scale bipartite graph and showed the alternate queries generated are better than those generated by popular search engines [25].”
Recommender Systems (2016, positive): “The work in [429] performs query recommendations with the use of random walks on the query-URL graph.”
Recommending interesting activity-related local entities (2011, background): “to the expected time before a random walk from reaches [3].”
Click-through-based cross-view learning for image search (2014, background): “proposed an approach to query suggestion by computing the hitting time on a click graph [19].”