Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Mashups for semantic user profiles
Proceedings of the 17th international conference on World Wide Web
Using linguistic cues for the automatic recognition of personality in conversation and text
Journal of Artificial Intelligence Research
Recommender Systems Handbook
Statistical Data Analysis: A Practical Guide
Statistical Data Analysis: A Practical Guide
Overview of the third international workshop on search and mining user-generated contents
Proceedings of the 20th ACM international conference on Information and knowledge management
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The appearance of the so-called recommender systems has led to the possibility of reducing the information overload experienced by individuals searching among online resources. One of the areas of application of recommender systems is the online tourism domain where sites like TripAdvisor allow people to post reviews of various hotels to help others make a good choice when planning their trip. As the number of such reviews grows in size every day, clearly it is impractical for the individual to go through all of them. We propose the TWIN ("Tell me What I Need") Personality-based Recommender System that analyzes the textual content of the reviews and estimates the personality of the user according to the Big Five model to suggest the reviews written by "twin-minded" people. In this paper we compare a number of algorithms to select the better option for personality estimation in the task of user profile construction.