-------- Forwarded Message -------- Subject: [AISWorld] Workshop on Explainable and Holistic User Modeling - ExHUM 2019@UMAP 2019 - Call for Papers Date: Thu, 21 Feb 2019 12:33:27 +0100 From: Cataldo Musto cataldo.musto@uniba.it To: aisworld@lists.aisnet.org

*** Apologies for cross postings ***

ExHUM Workshop @UMAP 2019 - CALL FOR PAPERS ---------------------------------------------------------------------- Explainable and Holistic User Modelling - Transparent Personalization Methods based on Heterogeneous Personal Data (ExHUM@UMAP 2019)

co-located with UMAP 2019 ( http://www.um.org/umap2019 http://www.um.org/umap2019) - Larnaca, Cyprus 9-12 June 2019

Twitter: https://twitter.com/ExHUM_Workshop https://twitter.com/ExHUM_Workshop Web: https://exhum19.wordpress.com/ https://exhum19.wordpress.com Submission: https://easychair.org/conferences/?conf=exhum2019 https://easychair.org/conferences/?conf=exhum2019 For any information: https://webmail.uniba.it/imp/dynamic.php?page=mailbox cataldo.musto@uniba.it; https://webmail.uniba.it/imp/dynamic.php?page=mailbox amon.rapp@gmail.com

========= ABSTRACT =========

According to a recent claim by IBM, 90% of the data available today have been created in the last two years. This exponential growth of personal information has given new life to research in the area of user modelling and personalization, since information about users' preferences, sentiment and opinions, as well as signals describing their physical and psychological state, can now be obtained by mining data gathered from many heterogeneous sources.

How can we use such data drive personalization and adaptation mechanisms? How can we effectively merge such data to obtain a holistic representation of all (or some of) the facets describing people? What kinds of usage scenarios can be envisioned? What kinds of services can be enabled by all these personal data?

Moreover, as the importance of such technologies in our everyday lives grows, it is also fundamental that the internal mechanisms that guide personalization algorithms are as clear as possible. It is not by chance that the recent General Data Protection Regulation (GDPR) emphasized the users' right to explanation when people face machine learning-based (or, generally speaking, artificial intelligence-based) systems. Unfortunately, the current research tends to go in the opposite direction, since most of the approaches try to maximize the effectiveness of the personalization strategy (e.g., recommendation accuracy) at the expense of the explainability and the transparency of the model.

Accordingly, other important questions arise: how we can deal with the dichotomy between the need for effective adaptive systems based on heterogeneous and personal data and the right to transparency and interpretability? Is it possible to design systems that merge several personal information and also guarantee a transparent and sctruable personalization strategy?

The workshop aims to provide a forum for discussing open problems, challenges and innovative research approaches in the area. Specificallt, 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 ====== 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

============ SUBMISSIONS ============ 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 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 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.

================ IMPORTANT DATES =============== * Full paper submission: March 13, 2019 * Paper notification: March 27, 2019 * Camera-ready paper: April 3, 2019

============= ORGANIZATION ============= Cataldo Musto - University of Bari, Italy Amon Rapp - University of Torino, Italy Federica Cena - University of Torino, Italy Frank Hopfgartner - University of Glasgow, UK Judy Kay - University of Sydney, Australia Aonghus Lawlor - University College Dublin, Ireland Pasquale Lops - University of Bari, Italy Giovanni Semeraro - University of Bari, Italy Nava Tintarev, Delft University of Technology, The Netherlands

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