An automatic procedure for generating datasets for conversational recommender systems

Alessandro Suglia, Claudio Greco, Pierpaolo Basile, Giovanni Semeraro, Annalina Caputo

Research output: Contribution to journalConference articlepeer-review

3 Citations (Scopus)

Abstract

Conversational Recommender Systems assist online users in their information-seeking and decision making tasks by supporting an interactive process with the aim of finding the most appealing items according to the user preferences. Unfortunately, collecting dialogues data to train these systems can be labour-intensive, especially for data-hungry Deep Learning models. Therefore, we propose an automatic procedure able to generate plausible dialogues from recommender systems datasets.

Original languageEnglish
Article number197
JournalCEUR Workshop Proceedings
Volume1866
Publication statusPublished - 13 Jul 2017
Event18th Working Notes of CLEF Conference and Labs of the Evaluation Forum 2017 - Dublin, Ireland
Duration: 11 Sep 201714 Sep 2017

ASJC Scopus subject areas

  • Computer Science(all)

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