[DL] [KaRS] Second CfP: 2nd Knowledge aware and Conversational Recommender Systems Workshop 2019
Vito Walter Anelli
vitowalter.anelli at poliba.it
Mon Jul 15 13:03:29 CEST 2019
*** Call for Papers ***
2nd Workshop on Knowledge aware and Conversational Recommender Systems - KaRS 2019
co-located with the 28th ACM International Conference on Information and Knowledge Management (CIKM)
November 3rd-7th, 2019, Beijing, China
-- SCOPE --
We are pleased to invite you to contribute to the Second Workshop on Knowledge-aware and Conversational Recommender Systems held in conjunction with the ACM International Conference on Information and Knowledge Management (CIKM 2019) Beijing, China, from November the 3rd to November the 7th, 2019.
Over the last years, 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 for 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 terms of accuracy of results, collaborative approaches miss some very interesting features that go beyond the accuracy of results and move into the direction of providing novel and diverse results as well as generate an explanation for the recommended items or support interactive and conversational recommendation processes.
This workshop will focus on all aspects related to the exploitation of external and explicit knowledge sources to feed a recommendation engine. The aim is to go beyond the traditional accuracy goal and to start a new generation of algorithms and approaches which exploit the knowledge encoded in ontological and logic-based knowledge bases, knowledge graphs as well as the semantics emerging from the analysis of semi-structured textual sources. The aim of the workshop 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, and
* identify emerging topics.
This workshop aims at establishing an interdisciplinary community with a focus on the exploitation of (semi-)structured knowledge for recommender systems and promoting the collaboration opportunities between researchers and practitioners. We particularly encourage demos and mock-ups of systems to be used as a basis of a lively and interactive discussion in the workshop.
Topics of interests include, but are not limited to:
* 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.)
* Deep learning methods to model semantic features
* Logic-based modeling of a recommendation process
* Knowledge Representation and Automated Reasoning for recommendation engines
* Knowledge-based and conversational recommender systems
* Using knowledge-bases and knowledge-graphs to increase recommendation quality(e.g., in terms of novelty, diversity, serendipity, or explainability)
* Knowledge-aware explanations to recommendations (compliant with the General Data Protection Regulation)
* Using knowledge sources for cross-lingual recommendations
* Knowledge-aware user modeling
* 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
* Methodological aspects (evaluation protocols, metrics, and data sets)
* Design of conversational agents
* Critiquing in conversational recommenders
* Question-asking in conversational recommenders
* Explanations in conversational recommenders
* Active learning in conversational recommenders
* User modeling 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
-- PAPER SUBMISSION CATEGORIES --
We encourage the submission of original contributions, which address novel interface issues in recommender systems.
* LONG PAPERS. should report on substantial contributions of lasting value. The maximum length is 6 pages (plus up to 1 page references). Each accepted long paper will be included in the CEUR on-line 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 strong theoretical foundation. Applications of recommender systems to novel areas are especially welcome. The maximum length is 3 pages (plus up to 1 page references). Each accepted short paper will be included in the CEUR on-line Workshop proceedings and presented in a poster session. The poster presentation may include a system demonstration. Selected short papers will be invited as oral presentations.
Submission page: https://easychair.org/conferences/?conf=kars2019
-- PAPER FORMAT AND SUBMISSION --
All submissions and reviews will be handled electronically. KaRS submissions should be prepared according to the standard double-column ACM SIG proceedings format. Additional information about formatting and style files is available online. Papers must be submitted to Easychair by 23:59, AoE (Anywhere on Earth) of the paper submission deadline below.
Submitted work should be original. Simultaneous submissions to other conferences or journals are explicitly prohibited by CEUR policies. However, technical reports or ArXiv disclosure prior to or simultaneous with KaRS submission is allowed, provided they are not peer-reviewed. Please refer to the CEUR Publication License Agreement for further details.
Please take note that the official publication date is the date the proceedings are made available in the CEUR Workshop Proceedings. This date may be up to two weeks prior to the first day of the conference. The official publication date affects the deadline for any patent filings related to published work.
Submitted papers will be evaluated according to their originality, technical content, style, clarity, and relevance to the workshop. For short papers we will encourage also alternative modes of presentation such as demos, playing out of scenarios, mock-ups, and alternate media such as video.
Demonstration sessions will provide the opportunity to show innovative interface designs for recommender systems.
-- IMPORTANT DATES --
* Paper submission deadline: August 12, 2019
* Author notification: September 2, 2019
* Camera-ready version deadline: September 6, 2019
Deadlines refer to 23:59 (11:59pm) in the AoE (Anywhere on Earth) time zone.
-- ORGANIZING COMMITTEE --
* Vito Walter Anelli, Polytechnic University of Bari
* Tommaso Di Noia, Polytechnic University of Bari
-- STEERING COMMITTEE --
* Vito Walter Anelli - Polytechnic University of Bari, Italy
* Tommaso Di Noia - Polytechnic University of Bari, Italy
* Pasquale Lops - Dept. of Computer Science, University of Bari Aldo Moro, Italy
* Cataldo Musto - Dept. of Computer Science, University of Bari Aldo Moro, Italy
* Markus Zanker - Free University of Bozen – Bolzano, Italy
* Pierpaolo Basile - Dept. of Computer Science, University of Bari Aldo Moro, Italy
* Derek Bridge - Insight Centre for Data Analytics, University College Cork
* Fedelucio Narducci - Dept. of Computer Science, University of Bari Aldo Moro, Italy
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