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Call for Papers
Third Workshop on Knowledge-aware and Conversational Recommender
Systems (KaRS 2021)
https://kars-workshop.github.io/2021/
http://sisinflab.poliba.it/kars/2021/
Sep. 27th - Oct. 1st, 2021, Amsterdam, the Netherlands
Submission deadline: July 29th, 2021, 2021 AoE
[SCOPE]
We are pleased to invite you to contribute to the Third Workshop
on Knowledge-aware and Conversational Recommender Systems held in
conjunction with the ACM International Conference on Recommender
Systems (RecSys 2021) Amsterdam, the Netherlands, from September
the 27th to October the 1st, 2021.
In the last few years, a renewed interest of the research
community on conversational recommender systems (CRSs) is
emerging. This is probably due to the great diffusion of Digital
Assistants (DAs) such as Amazon Alexa, Siri, or Google Assistant
that are revolutionizing the way users interact with machines. DAs
allow users to execute a wide range of actions through an
interaction mostly based on natural language messages.
However, although DAs are able to complete tasks such as sending
texts, making phone calls, or playing songs, they are still at an
early stage on offering recommendation capabilities by using the
conversational paradigm.
In addition, we have been witnessing the advent of more and more
precise and powerful recommendation algorithms and techniques able
to effectively assess users' tastes and predict information that
would probably be of interest to them.
Most of these approaches rely on the collaborative paradigm (often
exploiting machine learning techniques) and do not take into
account the huge amount of knowledge, both structured and
non-structured ones, describing the domain of interest of the
recommendation engine.
Although very effective in predicting relevant items,
collaborative approaches miss some very interesting features that
go beyond the accuracy of results and move in the direction of
providing novel and diverse results as well as generating an
explanation for the recommended items. Furthermore, this side
information becomes crucial when a conversational interaction is
implemented, in particular for the preference elicitation,
explanation, and critiquing steps.
The 3rd Knowledge-aware and Conversational Recommender Systems
(KaRS) Workshop focuses on all aspects related to the exploitation
of external and explicit knowledge sources to feed and build a
recommendation engine, and on the adoption of interactions based
on the conversational paradigm. The aim is to go beyond the
traditional accuracy goal and to start a new generation of
algorithms and approaches with the help of the methodological
diversity embodied in fields such as Machine Learning (ML),
Human-Computer Interaction (HCI), Information Retrieval (IR), and
Information Systems (IS). Consequently, the focus lies on works
improving the user experience and following goals such as user
engagement and satisfaction or customer value.
The aim of this third edition of KaRS is to bring together
researchers and practitioners around the topics of designing and
evaluating novel approaches for recommender systems in order to:
* share research and techniques, including new design technologies
and evaluation methodologies;
* identify next key challenges in the area;
* identify emerging topics in the field.
[TOPICS]
This workshop aims at establishing an interdisciplinary community
with a focus on the exploitation of (semi-)structured knowledge
and conversational approaches for recommender systems and
promoting collaboration opportunities between researchers and
practitioners.
Topics of interests include, but are not limited to:
- Knowledge-aware Recommender Systems.
- Models and Feature Engineering:
- Knowledge-aware data models based on structured knowledge
sources (e.g., Linked Open Data, BabelNet, Wikidata, etc.)
- Semantics-aware approaches exploiting the analysis of textual
sources (e.g., Wikipedia, Social Web, etc.)
- Knowledge-aware user modeling
- Methodological aspects (evaluation protocols, metrics, and data
sets)
- Logic-based modeling of a recommendation process
- Knowledge Representation and Automated Reasoning for
recommendation engines
- Deep learning methods to model semantic features
- Beyond-Accuracy Recommendation Quality:
- Using knowledge-bases and knowledge-graphs to increase
recommendation quality(e.g., in terms of novelty, diversity,
serendipity, or explainability)
- Explainable Recommender Systems
- Knowledge-aware explanations to recommendations (compliant with
the General Data Protection Regulation)
- Online Studies:
- Using knowledge sources for cross-lingual recommendations
- Applications of knowledge-aware recommenders (e.g., music or
news recommendation, off-mainstream application areas)
- User studies (e.g., on the user's perception of knowledge-based
recommendations), field studies, in-depth experimental offline
evaluations
- Conversational Recommender Systems.
- Design of a Conversational Agent:
- Design and implementation methodologies
- Dialogue management (end-to-end, dialog-state-tracker models)
- UX design
- Dialog protocols design
- User Modeling and interfaces:
- Critiquing and user's feedback exploitation
- Short- and Long-term user profiling and modeling
- Preference elicitation
- Natural language-, multi modal-, and voice-based interfaces
- Next-question problem
- Methodological and Theoretical aspects:
- Evaluation and metrics
- Datasets
- Theoretical aspects of conversational recommender systems
[SUBMISSIONS]
Submissions of full research papers must be in English, in PDF
format in the CEUR-WS two-column conference format available at:
http://ceur-ws.org/Vol-XXX/CEURART.zip
or at:
https://www.overleaf.com/latex/templates/template-for-submissions-to-ceur-workshop-proceedings-ceur-ws-dot-org/hpvjjzhjxzjk
if an Overleaf template is preferred.
Submission will be peer-reviewed and accepted papers will appear
in the CEUR workshop series. Papers may range from theoretical
works to system descriptions.
We particularly encourage Ph.D. students or Early-Stage
Researchers to submit their research. We also welcome
contributions from the industry and papers describing ongoing
funded projects which may result useful to the Knowledge-aware and
Conversational Recommender Systems community.
The conference language is English.
We invite three kinds of submissions, which address novel issues
in Knowledge-aware and Conversational Recommender Systems:
* Long Papers should report on substantial contributions of
lasting value. The Long papers must have a length of a minimum of
6 and a maximum of 8 pages (plus an unlimited number of pages for
references). Each accepted long paper will be included in the CEUR
online Workshop proceedings and presented in a plenary session as
part of the Workshop program.
* Short/Demo Papers typically discuss exciting new work that is
not yet mature enough for a long paper. In particular, novel but
significant proposals will be considered for acceptance to this
category despite not having gone through sufficient experimental
validation or lacking a strong theoretical foundation.
Applications of recommender systems to novel areas are especially
welcome. The Short/Demo papers must have a length of a minimum of
3 and a maximum of 5 pages (plus an unlimited number of pages for
references). Each accepted short paper will be included in the
CEUR online Workshop proceedings
* Position/Discussion Papers describe novel and innovative ideas.
Position papers may also comprise an analysis of currently
unsolved problems, or review these problems from a new
perspective, in order to contribute to a better understanding of
these problems in the research community. We expect that such
papers will guide future research by highlighting critical
assumptions, motivating the difficulty of a certain problem, or
explaining why current techniques are not sufficient, possibly
corroborated by quantitative and qualitative arguments. The
Position/Discussion papers must have a length of a minimum of 2
and a maximum of 3 pages (plus an unlimited number of pages for
references). Original Position/Discussion accepted papers will be
included in the CEUR online Workshop proceedings. Selected
Position/Discussion papers will be invited as oral presentations.
The review process is single-blind. Submitted papers will be
evaluated according to their originality, technical content,
style, clarity, and relevance to the workshop.
Moreover, following the RecSys 2021 guidelines, reviewers will be
asked to comment on whether the length is appropriate for the
contribution. Shorter papers should generally report on advances
that can be described, set into context, and evaluated concisely.
Longer papers should reflect substantial contributions of lasting
value.
Short and long paper submissions must be original work and may not
be under submission to another venue at the time of review.
Accepted papers will appear in the workshop proceedings.
Submission will be through Easychair at:
https://easychair.org/conferences/?conf=kars2021
[IMPORTANT DATES]
* Paper submissions due: July 29th, 2021
* Paper acceptance notification: August 21st, 2021
* Camera-ready deadline: August 28th, 2021
* Workshop day: Sep 27th - Oct 1st, 2021
Deadlines refer to 23:59 (11:59pm) in the AoE (Anywhere on Earth)
time zone.
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