Context-aware and multilingual information extraction for a tourist recommender system

Authors:
Ago Luberg;Priit Järv;Karin Schoefegger;Tanel Tammet
Affiliations:
Estonia Tallinn University of Technology, Ehitajate tee, Tallinn, Estonia;Estonia Tallinn University of Technology, Ehitajate tee, Tallinn, Estonia;Graz University of Technology, Inffeldgasse, Graz Austria;Estonia Tallinn University of Technology, Ehitajate tee, Tallinn, Estonia
Venue:
i-KNOW '11 Proceedings of the 11th International Conference on Knowledge Management and Knowledge Technologies
Year:
2011

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Abstract

We present information extraction for a semantic personalised tourist recommender system. The main challenges in this setting are that information is spread across various information sources, it is usually stored in proprietary formats and is available in different languages in varying degrees of accuracy. We address the mentioned challenges and describe our realization and ideas how to deal with each of them. In our paper we describe scraping and extracting keywords from different web portals with different languages, how we deal with missing multi-lingual data, and how we identify the same objects from different sources.