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Mining user activity as a context source for search and retrieval

Qiu, Zhengwei and Doherty, Aiden R. and Gurrin, Cathal and Smeaton, Alan F. (2011) Mining user activity as a context source for search and retrieval. In: STAIR'11: International Conference on Semantic Technology and Information Retrieval, 28-29 June 2011, Kuala Lumpur, Malaysia.

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Nowadays in information retrieval it is generally accepted that if we can better understand the context of users then this could help the search process, either at indexing time by including more metadata or at retrieval time by better modelling the user context. In this work we explore how activity recognition from tri-axial accelerometers can be employed to model a user's activity as a means of enabling context-aware information retrieval. In this paper we discuss how we can gather user activity automatically as a context source from a wearable mobile device and we evaluate the accuracy of our proposed user activity recognition algorithm. Our technique can recognise four kinds of activities which can be used to model part of an individual's current context. We discuss promising experimental results, possible approaches to improve our algorithms, and the impact of this work in modelling user context toward enhanced search and retrieval.

Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Uncontrolled Keywords:context; sensecam
Subjects:Computer Science > Information retrieval
DCU Faculties and Centres:Research Initiatives and Centres > Centre for Digital Video Processing (CDVP)
Research Initiatives and Centres > CLARITY: The Centre for Sensor Web Technologies
DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Science Foundation Ireland
ID Code:16479
Deposited On:05 Aug 2011 15:14 by Zhengwei Qiu. Last Modified 17 Feb 2017 10:00

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