Recommending Personalized Summaries of Teaching Materials

Recommending Personalized Query Revisions

Observing the queries selected by a user, among those suggested by a recommender system, one can infer constraints on the user’s utility function, and can avoid suggesting queries that retrieve products with an inferior utility, i.e., dominated queries. In this paper we propose a new efficient technique for the computation of dominated queries. It relies on the system’s assumption that the numb...

Creating Dynamic, Personalized RSS Summaries

Automatically generated, human-quality text summarization systems are difficult both to develop and to evaluate, partly because articles differ along several dimensions: length, writing style and lexical usage. In this paper we propose a framework that, by utilizing RSS feeds, is able to personalize on the needs of the users and on the needs of their device, in order to present to the end-user ...

RECOMMENDING AS PERSONALIZED TEACHING Towards Credible Needs-based eCommerce Recommender Systems

A Method for Building Personalized Ontology Summaries

In the context of ontology engineering, the ontology understanding is the basis for its further development and reuse. One intuitive effective approach to support ontology understanding is the process of ontology summarization which highlights the most important concepts of an ontology. Ontology summarization identifies an excerpt from an ontology that contains the most relevant concepts and pr...

Multi-sensored Vision for Autonomous Production of Personalized Video Summaries

Democratic and personalized production of multimedia content is a challenge that content providers will have to face in the near future. In this talk, we explain how it is possible to address this challenge by building on computer vision tools to automate the collection and distribution of audiovisual content. In a typical application scenario, the sensor network for media acquisition is compos...