[DL] UMUAI Special Issue "Conversational Recommender Systems: Theory, Models, Evaluations, and Trends"

[Vito Walter Anelli]

(Apologies for multiples posting. Appreciate if you can distribute this CFP in your network)
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CFP Special Issue
*Conversational Recommender Systems: Theory, Models, Evaluations, and Trends*
User Modeling and User-Adapted Interaction (UMUAI) - Springer Journal (IF 4.230 @ 2021)
Special issue website: bit.ly/3FEL6ch
Springer journal website: https://link.springer.com/collections/cjgbcbdgig
*ABSTRACT DEADLINE: 15th of February 2023*
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= CALL FOR PAPERS =
In the last few years, a renewed interest of the research community in conversational recommender systems (CRSs) is emerging. This is likely due to the massive proliferation of Digital Assistants (DAs) such as Amazon Alexa, Siri, or Google Assistant, which are revolutionizing how people interact with machines.
DAs allow users to execute various actions through interactions primarily based on natural language utterances. However, although DAs are able to complete tasks such as sending texts, making phone calls, or playing songs, they remain at an early stage in terms of their recommendation-offering capabilities using the conversational paradigm. Very few studies investigated the theory behind conversational recommendations in terms of strategies and algorithms, complexity analysis, and so on.
Furthermore, since the recommendation becomes an incremental process where the user refines her request at each step to reach the recommendation goal, CRSs need to be powered with knowledge about the domain of the recommended items. Knowledge can be represented in different forms, such as structured information, unstructured one, knowledge graphs, etc.
Finally, the evaluation of CRSs is a crucial and non-conventional step, since it goes beyond the accuracy of results and moves in the direction of providing novel and diverse results, generating explanations for recommended items, reducing the user effort for reaching a liked item (e.g., in terms of exchanged messages), and often requires designing a user study.

= SPECIAL ISSUE TOPICS =
We are interested in contributions focusing on different new and relevant aspects of conversational recommender systems, in particular, new developments on the algorithmic and user interface level as well as new applications, all accompanied by a corresponding evaluation (e.g., empirical study) that clearly shows significant improvements compared to the state of the art.
The general topics regarded as relevant for the special issue on Conversational Recommender Systems include but are not limited to:

Methodological aspects of a Conversational Recommender Systems (CRS)
Design and implementation methodologies
Dialogue management (end-to-end, dialogue-state-tracker
models, retrieval-based, hybrid)
Recommendation algorithms for CRS
Multi-objective recommendations for CRS
Dialogue protocol design
Next-question problem
Knowledge bases and knowledge graphs for CRS
Explainable CRS
User Modeling and Interfaces for CRS
Short- and Long-term user profiling and modeling
Preference elicitation
Critiquing and user feedback elicitation
UX design
Natural language, multimodal, and voice-based interfaces
Theoretical aspects and conceptual aspects of CRS
Evaluation of CRS
User studies
Online experiments
Metrics beyond accuracy
Datasets

= IMPORTANT DATES =
Abstract submission: February 15, 2023
Abstract notification: February 28, 2023
Paper submission: April 15, 2023
Author notification: July 1, 2023
Revised paper submission: July 25, 2023
Final notification: August 25, 2023
Camera-ready paper submission: October 15, 2023
All deadlines are 11:59pm, AoE time (Anywhere on Earth).

= GUEST EDITORS =
Vito Walter Anelli, Polytechnic University of Bari (Italy)
Li Chen, Hong Kong Baptist University (China)
Gerard de Melo, University of Potsdam (Germany)
Julian McAuley, University of California (USA)
Fedelucio Narducci, Polytechnic University of Bari (Italy)
Azzurra Ragone, University of Bari Aldo Moro (Italy)

= SUBMISSION AND REVIEW DETAILS =
Please refer to the website: bit.ly/3FEL6ch
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