Contextual Data Analysis in Online Hotel Businesses

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Kookhahi, Ahmad | 2020

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Type of Document: M.Sc. Thesis
Language: Farsi
Document No: 53278 (01)
University: Sharif University of Technology
Department: Industrial Engineering
Advisor(s): Rafiee, Majid
Abstract:
in this study we intend to build a recommender system, more specifically We try to build a multi-criteria collaborative filtering. Collaborative filtering is one of the methods used in building of recommender systems. In this study, we use technical attributes to build a recommender system. Technical attributes refer to the attributes which focus on the writing style of the texts. After building the recommender system based on technical attributes, we also build a recommender system based on the conventional criteria in order to make a comparison between these two criteria. Collaborative filtering consists two major categories, namely memory-based and model-based that both of them have been used in our recommender system. Finally, we determine which of these criteria has a better performance
Keywords:
Text Mining ; Data Analysis ; Recommender System ; Online Businesses ; Collaborative Filtering ; Hoteling