InLinx for document classification, sharing and recommendation

We propose a hybrid recommender system, InLinx, that combines content analysis and the development of virtual clusters of students and of didactical sources providing facilities to use the huge amount of digital information according to the student's personal requirements and interests. Novel methods for information management, with special focus on the development of new algorithms and intelligent applications for personalized information sharing, filtering and retrieval is proposed. InLinx helps the student to classify domain specific information found in the Web and saved as bookmarks, to recommend these documents to other students with similar interests and to periodically notify new potentially interesting documents.