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Lucio Narducci <[log in to unmask]>
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Lucio Narducci <[log in to unmask]>
Fri, 11 May 2018 17:25:51 +0200
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*** Apologies for multiple postings ***
1st International Workshop on REbooting the COnVErsational Recommender
Systems (Recover 2018):
To be held in Vancouver (Canada). Co-located with ACM Conference on
Recommender Systems 2018:

Consider a recommender which engages with its user to help her to articulate
her short- or longer-term preferences. Consider too a recommender which
invites the user to express an opinion about tentative recommendations in
order to guide the recommender in making further recommendations. In both
cases, there is a cycle of interactions between the user and the
recommender. We will refer to these as conversational recommenders, and they
are the topic of this workshop.
Note that the phrase 'conversational' as defined here neither implies, nor
excludes, recommenders that conduct dialogs in natural language. A
conversational recommender might converse in natural language, but it may
allow more constrained modes of user interaction too.
Research into conversational recommenders was a prominent strand in the late
1990s and early 2000s. Papers on preference elicitation through
question-asking and on recommendation critiquing ("like this but cheaper")
were common.
While research and development into conversational recommenders has never
gone away, it has certainly been less prominent for a while.But this seems
to be changing. There seems to be renewed interest in conversational
It is this renewed interest that furnishes the rationale for holding this
workshop at this time.

Topics of Interest

We will invite papers that pertain to the workshop theme including but not
limited to:
design of conversational agents
critiquing in conversational recommenders
question-asking in conversational recommenders
explanations in conversational recommenders
active learning in conversational recommenders
user modelling for conversational recommenders
natural language interaction with recommenders
natural language processing for conversational recommenders
speech interfaces for conversational recommenders
dialogue management for conversational recommenders
UX design for conversational recommenders
conversation analysis for conversational recommenders
chatbots for conversational recommenders
conversational group recommenders
interaction methods in conversational recommenders


Authors may submit fully-developed ideas and approaches as long papers (8
pages) and preliminary work as short papers (4 pages). For full details on
the submission format and procedure, see below. Papers will be selected
based on originality, quality, and ability to promote discussion. Accepted
papers will be included in the workshop proceedings and published by CEUR.
Extended versions of selected workshop papers may be included in a special
journal issue (TBD). At least one author of each accepted paper must attend
the workshop.

All submissions should be in English and should not have been published or
submitted for publication elsewhere. Papers should be formatted in the ACM
Proceedings Style 
( and submitted
via EasyChair (

Submissions will be published in the workshop proceedings (CEUR-WS).

Shared Task

In this edition of the workshop, we propose a shared task on Conversational
Recommender Systems. In particular, relying on the dataset proposed in [1],
we encourage participants to develop systems able to both recommend items
and converse with the user.
The proposed dataset contains automatically created dialogues from two
well-known datasets: MovieLens 1M and MovieTweetings. The generated dataset
is in JSON format and is split in validation, training and testing. This
dataset allows computing the performance of a conversational recommender in
terms of precision and dialogue accuracy measured through the BLEU measure.
The dataset is available here:

A description of a system that uses these datasets is reported in [2].
[1] Alessandro Suglia, Claudio Greco, Pierpaolo Basile, Giovanni Semeraro
and Annalina Caputo. An automatic procedure for generating datasets for
conversational recommender systems. In Proceedings of Dynamic Search for
Complex Tasks-8th International Conference of the CLEF Association, CLEF.

[2] Claudio Greco, Alessandro Suglia, Pierpaolo Basile and Giovanni
Semeraro. Converse-Et-Impera: Exploiting Deep Learning and Hierarchical
Reinforcement Learning for Conversational Recommender Systems. In
Proceedings of 16th International Conference of the Italian Association for
Artificial Intelligence, 372-386, Springer 2017

Important dates
Paper submission deadline: July 16th, 2018
Author notification: July 31th, 2018
Camera-ready version deadline: August 4th, 2018
Workshop (at RecSys 2018): October 2-7, 2018

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