Advances in Affect- and Personality-based Personalized Systems
A special issue of Computers (ISSN 2073-431X).
Deadline for manuscript submissions: closed (8 January 2017) | Viewed by 15808
Special Issue Editors
Interests: recommender systems; affective computing; affective user modeling; personality computing
Interests: human–computer interaction; natural language generation; user modeling; agent-based systems
Interests: intelligent information access; personalization; information retrieval; semantic web
Interests: user-adapted communicatons; user modeling; context-aware recommender systems; social networks; statistical signal processing; optimization of communication systems
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Special Issue Information
Dear Colleagues,
Personality and emotions shape our daily lives by having a strong influence on our preferences, decisions, and behaviour in general. In recent years, emotions and personality have shown to play an important role in various aspects of personalized systems, such as implicit feedback, contextual information, affective content labelling, cold-start problem, diversity, cross-domain recommendations, group recommendations, e-learning, conversational systems, music information retrieval, etc. With the development of robust techniques for the unobtrusive acquisition of emotions (e.g., from various modalities, such as video or physiological sensors) and personality (e.g., from social media) the time is right to take advantage of these possibilities to collect massive datasets and improve recommender systems.
We invite you to submit the outcomes of your work on the above topics to this Special Issue. The goal of the Special Issue is to make available the knowledge that builds on recent advances, such as the ones presented at the EMPIRE workshop series (https://empire2016recsys.wordpress.com/).
Dr. Marko Tkalcic
Dr. Berardina De Carolis
Dr. Marco de Gemmis
Prof. Andrej Kosir
Guest Editors
Manuscript Submission Information
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Keywords
- Usage of affect (mood/emotions) in personalization
- Usage of personality in personalization
- Acquisition of personality and affect for personalized systems
- Evaluation of personalized systems based on affect and/or personality
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