User Profile Construction in the TWIN Personality-based Recommender System
Alexandra Roshchina, John Cardiff, Paolo Rosso · Arrow - TU Dublin (Technological University Dublin) · 2011
The information overload experienced by people who use online services and read usergenerated content (e.g. product reviews and ratings) to make their decisions has led to the development of the so-called recommender systems. We address the problem of the large increase in the user-generated reviews, which are added to each day and consequently make it difficult for the user to obtain a clear picture of the quality of the facility in which they are interested. In this paper, we describe the TWIN (“Tell me What I Need”) personality-based recommender system, the aim of which is to select for the user reviews which have been written by like-minded individuals. We focus in particular on the task of User Profile construction. We apply the system in the travelling domain, to suggest hotels from the TripAdvisor 1 site by filtering out reviews produced by people with similar, or like-minded views, to those of the user. In order to establish the similarity between people we construct a user profile by modelling the user’s personality (according to the Big Five model) based on linguistic cues collected from the user-generated text. 1