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Abstract
Search behavior, and information seeking behavior more generally, is often motivated by tasks that prompt search processes that are often lengthy, iterative, and intermittent, and are characterized by distinct stages, shifting goals and multitasking. Current search systems do not provide adequate support for users tackling complex tasks due to which the cognitive burden of keeping track of such tasks is placed on the searcher. In this note, we summarize our recent efforts towards extracting search tasks from search logs. Based on recent advancements in Bayesian Nonparametrics and distributional semantics, we propose novel algorithms to extract task and subtasks from a query collection. The models discussed can inform the design of the next generation of task-based search systems that leverage user’s task behavior for better support and personalization.
Original language | American English |
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Title of host publication | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
Editors | Björn Bringmann, Elisa Fromont, Nikolaj Tatti, Volker Tresp, Pauli Miettinen, Bettina Berendt, Gemma Garriga |
Publisher | Springer Verlag |
Pages | 284-288 |
Number of pages | 5 |
ISBN (Print) | 9783319461304 |
DOIs | |
State | Published - 2016 |
Event | 15th European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2016 - Riva del Garda, Italy Duration: Sep 19 2016 → Sep 23 2016 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 9853 LNCS |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | 15th European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2016 |
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Country/Territory | Italy |
City | Riva del Garda |
Period | 09/19/16 → 09/23/16 |
Fingerprint
Dive into the research topics of 'Query log mining for inferring user tasks and needs'. Together they form a unique fingerprint.Projects
- 1 Finished
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Dynamic User Interests
Liang, S. (CoI), Ren, Z. (CoI), Zhao, Y. (CoI), Yilmaz, E. (CoI), Kanoulas, E. (CoI), Ma, J. (CoI), De Rijke, M. (CoI) & Hobby, M. (CoI)
08/1/15 → 07/1/19
Project: Research