Special Issue on Knowledge Discovery and User Modelling for Smart Cities

Personal and Ubiquitous Computing Journal (Springer - ISSN: 1617-4917)

Aim and Scope

User modelling and personalization are commonly used in multiple tasks, in which users are characterized based only on explicit information about their knowledge, behaviour, social relations or preferences, aiming at adapting generic systems to the particularities of each user. The ubiquitousness of social networking sites, and mobile and smart-devices offers new information sources, opportunities and challenges for changing the personalisation paradigm.

In conjunction, the analysis of new data sources (such as social media and smart devices, amongst others) offers new research opportunities across a wide variety of disciplines, including media and communication studies, linguistics, sociology, health, psychology, information and computer sciences, or education. This allows to mine and analyse user behaviour aiming at discovering knowledge that would allow to better understand users (and ourselves), and thereby create more accurate models and personalisation strategies. Hence, a significant need arises for further development of innovative methods and approaches that are able to mine and deal with such new data sources, which has important implications in the context of inclusive eGovernment and Smart Cities. In this context, applications could leverage on the user’s models to design and tailor services according to the characteristics and needs of each particular citizen.

The aim of this special issue is to explore recent advances in mining and understanding data generated by citizens, as well as how to tackle the new challenges that arise. For example, the process of knowledge discovery, the long-term availability of data, the interpretation of user-generated information, ethical and legal considerations, the heterogeneous nature of information, the high volume of available data, and the creation of long-term user models that adapt to the dynamics of life, amongst others.

The special issue solicits original research contributions from academia and industry in the form of theoretical foundations, experimental and methodological developments, comparative analyses, experiments and case studies in the field.

Topics of interest

This special issue looks for contributions addressing a variety of research questions involved in the areas of lifelong user modelling and personalization in the context of smart cities. Topics of interest include but are not limited to:

• Techniques for collection, aggregation and analysis of Personal, Linked and Social Data.
• Semantics Representation of the mined data.
• Big data, scalability issues and technologies for massive social data extraction.
• Lifelogging techniques, sensor networks, wearable devices for collecting user information such as behaviour or biometric data.
• Tracking implicit feedback (e.g. social activities) to infer user interests.
• User, group and family modelling in eGovernment and Smart Cities.
• Mining of user behaviour, opinion mining, and sentiment analysis in eGovernment and Smart Citizens.
• Gamification and/or Crowdsourcing for mining citizens’ profiles and opinions
• User awareness and control over their own data.
• Ethical issues, need for transparency, privacy management of Personal and Social data.
• Recommender Systems based on lifelogging and social data, physiological data, emotions or behaviour.
• Lifelogging applications in computational social sciences.
• Approaches for the personalization of inclusive, personal and interactive services to citizens.
• Citizen-centred service design and modelling.
• Smart-cities data mining case studies.
• Modelling, analysis and knowledge extraction of users’ social interactions in mobile and pervasive social networks.
• Experimental platforms for social interaction in smart cities.

Submission

Please submit a full-length paper through the journal online submission system (http://www.editorialmanager.com/pauc/default.aspx) and indicate it is to this special issue. Papers should be formatted by following PAUC manuscript formatting guidelines.

For any submission that has partly published in KDD-UMCit 2018 or other conferences, we request authors to have at least 30% extension of their original papers and mention the original article in the cover letter. The submission procedure will be managed by the guest editors, strictly following the rules of PAUC.

Guest Editors

• Dr. Marcelo G. Armentano, ISISTAN, CONICET-UNICEN, Argentina
• Dr. Frank Hopfgartner, University of Sheffield, United Kingdom
• Dr. Ioanna Lykourentzou, Utrecht University, Netherlands
• Dr. Antonela Tommasel, ISISTAN, CONICET-UNICEN, Argentina

Important dates

NEW Submission deadline: October 30, 2018 November 30, 2018

• First Notification: Jan 15, 2019
• Revisions Due: Feb 15, 2019
• Final Notification: April 1, 2019