Summary of the paper

Title Evaluating the Similarity Estimator component of the TWIN Personality-based Recommender System
Authors Alexandra Roshchina, John Cardiff and Paolo Rosso
Abstract With the constant increase in the amount of information available in online communities, the task of building an appropriate Recommender System to support the user in her decision making process is becoming more and more challenging. In addition to the classical collaborative filtering and content based approaches, taking into account ratings, preferences and demographic characteristics of the users, a new type of Recommender System, based on personality parameters, has been emerging recently. In this paper we describe the TWIN (Tell Me What I Need) Personality Based Recommender System, and report on our experiments and experiences of utilizing techniques which allow the extraction of the personality type from text (following the Big Five model popular in the psychological research). We estimate the possibility of constructing the personality-based Recommender System that does not require users to fill in personality questionnaires. We are applying the proposed system in the online travelling domain to perform TripAdvisor hotels recommendation by analysing the text of user generated reviews, which are freely accessible from the community website.
Topics Text mining, Tools, systems, applications, Statistical and machine learning methods
Full paper Evaluating the Similarity Estimator component of the TWIN Personality-based Recommender System
Bibtex @InProceedings{ROSHCHINA12.1080,
  author = {Alexandra Roshchina and John Cardiff and Paolo Rosso},
  title = {Evaluating the Similarity Estimator component of the TWIN Personality-based Recommender System},
  booktitle = {Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12)},
  year = {2012},
  month = {may},
  date = {23-25},
  address = {Istanbul, Turkey},
  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Mehmet Uğur Doğan and Bente Maegaard and Joseph Mariani and Asuncion Moreno and Jan Odijk and Stelios Piperidis},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {978-2-9517408-7-7},
  language = {english}
 }
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