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RelMobIR - Relevance Criteria Combination for Mobile Information Retrieval



Crestani F.


Alian Nejadi M.



With the tremendous increase in the use of mobile phones worldwide recent years have seen a great increase in their use to access information on the web. While all major search engines have released versions of their search platforms for mobile phones, their performance has not seen as great an increase as we whould have expected. In fact, while mobile phones seem to provide great opportunities for more effective IR, given their greater personalisation and localisation capabilities, the theoretical work behind the effective use of these characteristics has been lagging behind. So, while a few researchers worldwide have recognised the potential and have started working on context-awareness for mobile IR, their progress on a very important aspect of this area of research has been slow. This proposal aims at addressing this fundamental aspect: relevance. This proposal addresses the problem of combining relevance criteria for mobile IR, in order to determine the effective overall relevance of a document to a user information need. The work proposed will start by addressing how to best estimate these different relevance criteria for a document, given what is know of the user’s opinions, preferences and his spatio-temporal context. It will then address the problem of the best combination of these relevance estimates, under the assumption of their independence from each other. The system will be progressively improved removing this simplifying assumptions.

Informazioni aggiuntive

Data d'inizio
Data di fine
48 Mesi
Enti finanziatori
Swiss National Science Foundation / Project Funding / Mathematics, Natural and Engineering Sciences (Division II)