Event-Based Recognition of Lived Experiences in User Reviews

Conference paper

DOI: 10.1007/978-3-319-49004-5_21

Part of the Lecture Notes in Computer Science book series (LNCS, volume 10024)
Cite this paper as:
Hassan E., Buscaldi D., Gangemi A. (2016) Event-Based Recognition of Lived Experiences in User Reviews. In: Blomqvist E., Ciancarini P., Poggi F., Vitali F. (eds) Knowledge Engineering and Knowledge Management. EKAW 2016. Lecture Notes in Computer Science, vol 10024. Springer, Cham

Abstract

User reviews on the web are an important source of opinions on products and services. For a popular product or service, the number of reviews can be large. Therefore, it may be difficult for a potential customer to read all of them and make a decision. We hypothesize and test if lived experiences from reviews may support the confidence of a user in a review. We identify and extract such lived experiences with a novel technique based on machine reading. Our experimental results demonstrate the effectiveness of the technique.

Keywords

Lived experiences extraction Event extraction Machine reading Semantic web User reviews 

Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  1. 1.LIPN, Université Paris XIII, CNRS UMR 7030VilletaneuseFrance
  2. 2.STLab, ISTC-CNRRomeItaly

Personalised recommendations