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Erschienen in:
2014 | OriginalPaper | Buchkapitel
ActMiner: Discovering Location-Specific Activities from Community-Authored Reviews
verfasst von : Sahisnu Mazumder, Dhaval Patel, Sameep Mehta
Erschienen in: Data Warehousing and Knowledge Discovery
Verlag: Springer International Publishing
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Location-specific community authored reviews are useful resource for discovering location-specific activities and developing various location-aware activity recommendation applications. Existing works on activity discovery have mostly utilized body-worn sensors, images or human GPS traces and discovered generalized activities that do not convey any location-specific knowledge. Moreover, many of the discovered activities are irrelevant and redundant and hence, significantly affect the performance of a location-aware activity recommender system. In this paper, we propose a three-phase Discover-Filer-Merge solution, namely
ActMiner
, to infer the location-specific relevant and non-redundant activities from community-authored reviews. The proposed solution uses Dependency-aware, Category-aware and Sense-aware approaches in three sequential phases to accomplish its objective. Experimental results on two real-world data sets show that the accuracy and correctness of
ActMiner
are better than the existing approaches.