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Annals of Computer Science and Information Systems, Volume 9

Position Papers of the 2016 Federated Conference on Computer Science and Information Systems

Daily Touristic Plan Recommendation Using Text Mining

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DOI: http://dx.doi.org/10.15439/2016F594

Citation: Position Papers of the 2016 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 9, pages 41–48 ()

Full text

Abstract. This study focuses on the proposal of a recommender system for daily touristic plans. In order to construct such a system it is further examined that there is a need of text mining applications. Moreover, Sentiment Analysis and Keyword Extraction techniques are evaluated by developing and testing different approaches. Sentiment Analysis approaches are examined step-by-step in order to pick the best among them to score restaurant data. Similarly, Keyword Extraction is evaluated from various perspectives of statistics, visualization and machine learning. By the end of the paper the structure and the flow of the proposed system is illustrated upon the chosen approaches which were tested throughout this paper

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