NDLI: Behavior-driven clustering of queries into topics

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Behavior-driven clustering of queries into topics

Content Provider	ACM Digital Library
Author	Donato, Debora Aiello, Luca Maria Menczer, Filippo Ozertem, Umut
Abstract	Categorization of web-search queries in semantically coherent topics is a crucial task to understand the interest trends of search engine users and, therefore, to provide more intelligent personalization services. Query clustering usually relies on lexical and clickthrough data, while the information originating from the user actions in submitting their queries is currently neglected. In particular, the intent that drives users to submit their requests is an important element for meaningful aggregation of queries. We propose a new intent-centric notion of topical query clusters and we define a query clustering technique that differs from existing algorithms in both methodology and nature of the resulting clusters. Our method extracts topics from the query log by merging missions, i.e., activity fragments that express a coherent user intent, on the basis of their topical affinity. Our approach works in a bottom-up way, without any a-priori knowledge of topical categorization, and produces good quality topics compared to state-of-the-art clustering techniques. It can also summarize topically-coherent missions that occur far away from each other, thus enabling a more compact user profiling on a topical basis. Furthermore, such a topical user profiling discriminates the stream of activity of a particular user from the activity of others, with a potential to predict future user search activity.
Starting Page	1373
Ending Page	1382
Page Count	10
File Format	PDF
ISBN	9781450307178
DOI	10.1145/2063576.2063775
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2011-10-24
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	User intent Mission Query log Topic User profiling
Content Type	Text
Resource Type	Article

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