An automatic procedure for generating datasets for conversational recommender systems

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

An automatic procedure for generating datasets for conversational recommender systems

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

Research output: Contribution to journal › Conference article › peer-review

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 language	English
Article number	197
Journal	CEUR Workshop Proceedings
Volume	1866
Publication status	Published - 13 Jul 2017
Event	18th Working Notes of CLEF Conference and Labs of the Evaluation Forum 2017 - Dublin, Ireland Duration: 11 Sept 2017 → 14 Sept 2017

ASJC Scopus subject areas

General Computer Science

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http://ceur-ws.org/Vol-1866/paper_197.pdf

Cite this

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title = "An automatic procedure for generating datasets for conversational recommender systems",

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.",

author = "Alessandro Suglia and Claudio Greco and Pierpaolo Basile and Giovanni Semeraro and Annalina Caputo",

year = "2017",

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T1 - An automatic procedure for generating datasets for conversational recommender systems

AU - Suglia, Alessandro

AU - Greco, Claudio

AU - Basile, Pierpaolo

AU - Semeraro, Giovanni

AU - Caputo, Annalina

PY - 2017/7/13

Y1 - 2017/7/13

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85034775036&partnerID=8YFLogxK

M3 - Conference article

AN - SCOPUS:85034775036

SN - 1613-0073

VL - 1866

JO - CEUR Workshop Proceedings

JF - CEUR Workshop Proceedings

M1 - 197

T2 - 18th Working Notes of CLEF Conference and Labs of the Evaluation Forum 2017

Y2 - 11 September 2017 through 14 September 2017

ER -

An automatic procedure for generating datasets for conversational recommender systems

Abstract

ASJC Scopus subject areas

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