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Implicit relevance feedback for context-aware information retrieval in UbiLearning environments
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Symposium on Applied Computing archive
Proceedings of the 2009 ACM symposium on Applied Computing table of contents
Honolulu, Hawaii
SESSION: Web technologies track table of contents
Pages 659-663  
Year of Publication: 2009
ISBN:978-1-60558-166-8
Authors
Diogo S. Martins  Universidade Federal de São Carlos, São Carlos -- SP -- Brazil
Mauro Biajiz  Universidade Federal de São Carlos, São Carlos -- SP -- Brazil
Antonio F. do Prado  Universidade Federal de São Carlos, São Carlos -- SP -- Brazil
Wanderley L. de Souza  Universidade Federal de São Carlos, São Carlos -- SP -- Brazil
Sponsor
SIGAPP: ACM Special Interest Group on Applied Computing
Publisher
ACM  New York, NY, USA
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ABSTRACT

Ubiquitous Learning (UbiLearning) environments heavily employ mobile devices to empower users with mobility and tooling support to learn anytime, anywhere. Introducing mobile devices in educational settings imposes constraints on search behavior due to limited resources on these devices such as small screens and restricted input functionalities. Targeting this scenario, this paper proposes an architecture for implicit relevance feedback which considers users' work context to expand search queries in order to satisfy information needs with greater precision. Evaluation results conducted over a local test collection enriched with contextual features reveal improvements on average precision when compared to a pseudo relevance feedback baseline.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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L. Freund and E. G. Toms. Contextual search: from information behaviour to information retrieval. Proc. of the Conference of the Canadian Assoc. for Inf. Science, 2005.
 
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R. Redon, A. Larsson, R. Leblond, and B. Longueville. Vivace context based search platform. Modeling and Using Context, pages 397--410, 2007.
 
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Collaborative Colleagues:
Diogo S. Martins: colleagues
Mauro Biajiz: colleagues
Antonio F. do Prado: colleagues
Wanderley L. de Souza: colleagues