Natural Language Processing Applied in Itinerary Recommender Systems

نویسندگان

  • ANDREEA DIOSTEANU
  • LIVIU ADRIAN COTFAS
چکیده

In this paper we present a mobile application based on a hybrid multi-objective genetic algorithm and Natural Language Processing that can be used by tourists to smartly generate itineraries. Besides allowing users to find interesting Points of Interest based on highly detailed information, the semantic search approach is also capable of providing recommendation without requiring a lot of information regarding the current user. A multi-objective genetic algorithm has been used in order to find Pareto-optimal solutions in near real-time for the itinerary problem. The proposed system requires minimum input from the user and it is easy to use, thus we can state that our solution is both complex and at the same time user-oriented. Key-Words: semantic similarity, free text document indexing, multi-objective genetic algorithm, itinerary recommender system

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تاریخ انتشار 2011