Ranking Hotel Reviews Based on User's Aspects Importance and Opinions

International audienceOnline product reviews have become fundamental to users' purchasing decisions. Many websites provide rating-based ranking of entities, but analyzing the set of textual reviews is still time-consuming. Indeed, each user (reader) must build his/her own judgment from the set of reviews of the other users (writers), who might not have the same expectations and needs. To speed up this process , work have proposed more personalized rankings, which are restricted to the writer's perspective. In this work, we present an approach to rank reviews of an entity of interest, a hotel, based on the reader's profile. The method extracts a profile from free-text reviews and uses it to assess the degree of relevance of each review to rank according to the user's interests. The results obtained in the experiment exhibit a Mean Reciprocal Rank (MRR) of 0.72%, which is higher than comparable approaches of the literature. This paper also emphasizes the lack of available material to undertake such research, and sketches a methodology for evaluation