TWIN: Personality-based Intelligent Recommender System

Article type: Research Article

Authors: Roshchina, Alexandra^a | Cardiff, John^{a; *} | Rosso, Paolo^b

Affiliations: [a] Social Media Research Group, Institute of Technology Tallaght Dublin, Ireland | [b] NLE Lab.-PRHLT Research Center, Universitat Politecnica de Valencia, Spain

Correspondence: [*] Correspondence to: John Cardiff, Social Media Research Group, Institute of Technology Tallaght Dublin, Ireland. Tel.: +35 31 4042858; Fax: +35 31 4042700; john.cardiff@ittdublin.ie

Abstract: This paper presents the “Tell me What I Need” (TWIN) Personality-based Intelligent Recommender System, the goal of which is to recommend items chosen by like-minded (or “twin”) people with similar personality types which we estimate from their writings. In order to produce recommendations it applies the results achieved in the personality from the text recognition research field to Personality-based Recommender System user profile modelling. In this way it creates a bridge between the efforts of automatic personality score estimation from plain text and the field of Intelligent Recommender Systems. The paper describes the TWIN system architecture, and results of the experimentation with the system in the online travelling domain in order to investigate the possibility of providing valuable recommendations of hotels of the TripAdvisor website for “like-minded people”. The results compare favourably with related experiments, although they demonstrate the complexity of this challenging task.

Keywords: Personality Recognition, Intelligent Recommender System, text processing, personality-based user model

DOI: 10.3233/IFS-141484

Journal: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 5, pp. 2059-2071, 2015