In this paper, we introduce BOTTARI: an augmented reality application that offers personalized and location-based recommendations of Point Of Interests based on sentiment analysis with geo-semantic query and reasoning. We present a mobile recommendation platform and application working on semantic technologies (knowledge representation and query for geo-social data, and inductive and deductive stream reasoning), and the lesson learned in deploying BOTTARI in Insadong. We have been collecting and analyzing tweets for three years to rate the few hundreds of restaurants in the district. The results of our study show the commercial feasibility of BOTTARI.

Location-Based Mobile Recommendations by Hybrid Reasoning on Social Media Streams

BALDUINI, MARCO;DELL'AGLIO, DANIELE;DELLA VALLE, EMANUELE
2013

Abstract

In this paper, we introduce BOTTARI: an augmented reality application that offers personalized and location-based recommendations of Point Of Interests based on sentiment analysis with geo-semantic query and reasoning. We present a mobile recommendation platform and application working on semantic technologies (knowledge representation and query for geo-social data, and inductive and deductive stream reasoning), and the lesson learned in deploying BOTTARI in Insadong. We have been collecting and analyzing tweets for three years to rate the few hundreds of restaurants in the district. The results of our study show the commercial feasibility of BOTTARI.
Semantic Technology - Third Joint International Conference, JIST 2013
9783319068251
9783319068268
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11311/869346
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