Designing Web Usability: The Practice of Simplicity
Designing Web Usability: The Practice of Simplicity
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Mining search engine query logs for social filtering-based query recommendation
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Inferring semantic query relations from collective user behavior
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A web search method based on the temporal relation of query keywords
WISE'06 Proceedings of the 7th international conference on Web Information Systems
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Time-sensitive query auto-completion
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Dimension independent similarity computation
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Using temporal bursts for query modeling
Information Retrieval
Investigating query bursts in a web search engine
Web Intelligence and Agent Systems
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We investigate the idea of finding semantically related search engine queries based on their temporal correlation; in other words, we infer that two queries are related if their popularities behave similarly over time. To this end, we first define a new measure of the temporal correlation of two queries based on the correlation coefficient of their frequency functions. We then conduct extensive experiments using our measure on two massive query streams from the MSN search engine, revealing that this technique can discover a wide range of semantically similar queries. Finally, we develop a method of efficiently finding the highest correlated queries for a given input query using far less space and time than the naive approach, making real-time implementation possible.