Event-Based Recognition of Lived Experiences in User Reviews

  • Ehab Hassan
  • Davide Buscaldi
  • Aldo Gangemi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10024)


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.


Lived experiences extraction Event extraction Machine reading Semantic web User reviews 



I would like to thank Dr. Mehwish Alam for her suggestions. This work is partially supported by a public grant overseen by the French National Research Agency (ANR) as part of the program “Investissements d’Avenir” (reference: ANR-10-LABX-0083).


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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

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

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