Situational-Context for Virtually Modeling the Elderly

The generalized aging of the population is incrementing the pressure over, frequently overextended, healthcare systems. This situations is even worse in underdeveloped, sparsely populated regions like Extremadura in Spain or Alentejo in Portugal. In this paper we propose an initial approach to use the Situational-Context, a technique to seamlessly adapt Internet of Things systems to the needs and preferences of their users, for virtually modeling the elderly. These models could be used to enhance the elderly experience when using those kind of systems without raising the need for technical skills. The proposed virtual models will also be the basis for further eldercare innovations in sparsely populated regions

Automated user modeling for personalized digital libraries

Digital libraries (DL) have become one of the most typical ways of accessing any kind of digitalized information. Due to this key role, users welcome any improvements on the services they receive from digital libraries. One trend used to improve digital services is through personalization. Up to now, the most common approach for personalization in digital libraries has been user-driven. Nevertheless, the design of efficient personalized services has to be done, at least in part, in an automatic way. In this context, machine learning techniques automate the process of constructing user models. This paper proposes a new approach to construct digital libraries that satisfy user’s necessity for information: Adaptive Digital Libraries, libraries that automatically learn user preferences and goals and personalize their interaction using this information

Propagating user interests in ontology-based user model

In this paper we address the problem of propagating user interests in ontology-based user models. Our ontology-based user model (OBUM) is devised as an overlay over the domain ontology. Using ontologies as the basis of the user profile allows the initial user behavior to be matched with existing concepts in the domain ontology. Such ontological approach to user profiling has been proven successful in addressing the cold-start problem in recommender systems, since it allows for propagation from a small number of initial concepts to other related domain concepts by exploiting the ontological structure of the domain. The main contribution of the paper is the novel algorithm for propagation of user interests which takes into account i) the ontological structure of the domain and, in particular, the level at which each domain item is found in the ontology; ii) the type of feedback provided by the user, and iii) the amount of past feedback provided for a certain domain object

Voices Raised, Issue 06

Included in this issue: Immaculate Mary; Grants augment women’s research; Mentoring grows; Women’s Studies take root in the neighborhood; Solution-oriented VP to retire; Muslim students strive to educate, support; Don’t let stress ruin your holidays; Dining services dishes up more than you’d expect; Marianist Images Across Campus; Confronting Disrespect: We Owe it to Each Other.https://ecommons.udayton.edu/wc_newsletter/1005/thumbnail.jp