CAREER: Next Generation Personalization Technologies

University Of Minnesota-Twin Cities, Minneapolis MN

Investigators

Abstract

Abstract: IIS-0546443 This project addresses the practical need to develop more advanced personalization and recommendation technologies. Although recommender systems represent the most researched and developed personalization technologies applicable in a variety of applications, most current-generation recommender systems focus on recommending items to users and represent user preferences for an item with a single rating, and therefore are not sufficient to capture the intricacies of some of the more complex settings. This project develops several enhancements necessary for the next generation of recommender systems, such as context awareness, multi-criteria ratings, rating aggregation, flexibility of recommendations, and non-intrusiveness. In particular, the proposed approach explores the synergies between the recommendation process and the multidimensional/OLAP data model and extends the traditional recommendation framework to incorporate the advanced capabilities in a systematic manner. Overall, this research project will make contributions to both theory and practice by developing new frameworks, models, algorithms, and implementations that provide effective ways to deal with information overload and promote access to relevant information. Technologies resulting from this research can bring a broad range of benefits in many areas, including business and electronic commerce, social settings, and education. In addition, research results will be incorporated in the undergraduate and graduate courses on Business Intelligence and Information Technologies at the University of Minnesota. The results will also be made available to scientific community through publications in refereed journals and conferences. In addition, the project website (http://ids.csom.umn.edu/faculty/gedas/NSFcareer/) will be used to disseminate the publications, datasets, software, and course materials that result from this project.