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Context modelling for just-in-time mobile information retrieval (JIT-MobIR)
Az Azrinudin Alidin1, Crestani, Fabio2.
Mobile users have the capability of accessing information anywhere at any time with the introduction of mobile browsers and mobile web search. However, the current mobile browsers are implemented without considering the characteristics of mobile searches. As a result, mobile users need to devote time and effort in order to retrieve relevant information from the web in mobile devices. On the other hand, mobile users often request information related to their surroundings, which is also known as context. This recognizes the importance of including context in information retrieval. Besides, the availability of the embedded sensors in mobile devices has supported the recognition of context. In this study, the context acquisition and utilization for mobile information retrieval are proposed. The “just-in-time” approach is exploited in which the information that is relevant to a user is retrieved without the user requesting it. This will reduce the mobile user’s effort, time and interaction when retrieving information in mobile devices. In this paper, the context dimensions and context model are presented. Simple experiments are shown where user context is predicted using the context model.
Affiliation:
- Universiti Putra Malaysia, Malaysia
- Universita’ della Svizzera italiana, Switzerland
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Indexation |
Indexed by |
MyJurnal (2021) |
H-Index
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3 |
Immediacy Index
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0.000 |
Rank |
0 |
Indexed by |
Scopus 2020 |
Impact Factor
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CiteScore (1.1) |
Rank |
Q3 (Agricultural and Biological Sciences (all)) Q3 (Environmental Science (all)) Q3¬¬- (Computer Science (all)) Q3 (Chemical Engineering (all)) |
Additional Information |
SJR (0.174) |
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