Personalization Intelligence and Cooperativeness

Operation PIC: Personalization, Intelligence & Cooperativeness. This operation focuses on the problematic of exploiting and accessing data. Data can be precise or incomplete and include instances of ontological/semantic data, Web services, process models, etc. The activities of this operation are centered on the following topics.

  • Personalization: a first aspect is to investigate advanced models to represent and handle sophisticated user preferences; a second aspect deals with modeling and handling user context and profile to best fit its needs and desires.
  • Intelligence: modern-day database systems should exhibit intelligent behaviors to face the hugeness of data and the complexity of user needs. We study appropriate inference mechanisms to handle, for instance, inferred predicates/constructs and leverage knowledge discovery and machine learning techniques to intelligently answer database queries.
  • Cooperativeness: The aim is to develop novel approaches to cooperative query answering. We study query relaxation techniques to overcome the common problem of empty/unsatisfactory answers. We are also interested in other kind of cooperative responses such as intentional and summarized answers (in case of too many query results). 

Moreover, a particular effort is made about the scalability issue of the approaches developed. The theoretical tools used in this theme are mainly stemmed from fuzzy logic theory and domain ontologies.