The workshop aims to provide a forum for discussing open problems, challenges and innovative research approaches in the area. Specifically, we want to investigate:
(1) how to build a new generation of personalized and intelligent systems that exploit multiple data points (e.g., by combining mood data and music preferences data to provide recommendations on music to be listened)
(2) how to guarantee transparency and explainability in the user modeling, adaptation and personalization processes.
Topics of interests include but are not limited to:
- Transparent and Explainable Personalization Strategies
o Scrutable User Models
o Transparent User Profiling and Personal Data Extraction
o Explainable Personalization and Adaptation Methodologies
o Novel strategies (e.g., conversational recommender systems) for building transparent algorithms
o Transparent User Interfaces
o Designing Transparent Interaction methodologies - Designing and Evaluating Explanation Algorithms
o Explanation algorithms based on item description and item properties
o Explanation algorithms based on user-generated content (e.g., reviews)
o Explanation algorithms based on collaborative information
o Building explanation algorithms for opaque personalization techniques (e.g., neural networks, matrix factorization)
o Evaluating Transparency and Explainability in interaction or personalization
o Designing User Studies for evaluating transparency and explainability - Architectures for Holistic User Modeling
o Architectures for User Modeling merging heterogeneous data points
o User Modeling based on Semantic Content Analysis of Social and Linked Open Data
o User Modeling based on data coming from wearable devices
o User Modeling based on Emotions, physiology, and Personality Traits
o Lifelogging User Models - Novel Use Cases for Exploiting Personal and Heterogeneous Data
o Behavior change systems
o Health management systems
o Games and gamified applications
o Recommender systems
o e-Government domain
o Online Monitoring based on Social Data (Social CRM, Brand Analysis, etc.)
o Intelligent and Personalized Smart Cities-related Applications (e.g. Event Detection, Incident Detection, – Personalized Planners, etc.)
o Methodologies for including heterogeneous personal data in User Models - Open Issues in Transparent and Explainable User Models and Personalized Systems
o Ethical issues (Fairness and Biases) in User Models and Personalized Systems
o Privacy management of Personal and Social data
o Discussing Recent Regulations (GDPR) and future directions
o Tracking implicit feedbacks (e.g. social activities) to infer user interests
Submission
We encourage the submission of original contributions, investigating novel methodologies to exploit heterogeneous personal data and approach to build transparent and scrutable user models.
(A) Full research papers (max 4 pages + 1 reference – ACM format);
(B) Short Research papers and Demos (max 2 pages + 1 reference – ACM format);
Submission site: https://easychair.org/conferences/?conf=exhum2019
All submitted papers will be evaluated by at least two members of the program committee, based on originality, significance, relevance and technical quality. Papers should be formatted according to the ACM SIG proceedings template: http://www.acm.org/publications/proceedings-template
Note that the references do not count towards page limits. Submissions should be single blinded, i.e. authors names should be included in the submissions.
Submissions must be made through the EasyChair conference system prior the specified deadline (all deadlines refer to GMT). At least one of the authors should register and take part at the conference to make the presentation.
All accepted papers will be published by ACM as a joint volume of Extended UMAP 2019 Proceedings and will be available via the ACM Digital Library. At least one author of each accepted paper must register for the particular workshop and present the paper there.
For any information write to:
cataldo.musto@uniba.it; amon.rapp@gmail.com
Explainable and Holistic User Modeling 