Intent-aware temporal query modeling for keyword suggestion
Paper in proceeding, 2012

This paper presents a data-driven approach for capturing the temporal variations in user search behaviour by modeling the dynamic query relationships using query-log data. The dependence between different queries (in terms of the query words and latent user intent) is represented using hypergraphs which allows us to explore more complex relationships compared to graph-based approaches. This timevarying dependence is modeled using the framework of probabilistic graphical models. The inferred interactions are used for query keyword suggestion - a key task in web information retrieval. Preliminary experiments using query logs collected from internal search engine of a large health care organization yield promising results. In particular, our model is able to capture temporal variations between queries relationships that reflect known trends in disease occurrence. Further, hypergraph-based modeling captures relationships significantly better compared to graph-based approaches.

Keyword suggestion

Dynamic query interaction

Graphical model

User intent

Query hypergraph


Fredrik Johansson

Chalmers, Computer Science and Engineering (Chalmers), Computing Science (Chalmers)

Tobias Färdig

Chalmers, Computer Science and Engineering (Chalmers)

Vinay Jethava

Chalmers, Computer Science and Engineering (Chalmers), Computing Science (Chalmers)

S. Marinov


International Conference on Information and Knowledge Management, Proceedings

978-145031719-1 (ISBN)

Subject Categories

Electrical Engineering, Electronic Engineering, Information Engineering





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