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. © 2003 IEEE.
InLinx for document classification, sharing and recommendation / Bighini C.; Carbonaro A.; Casadei G.. - STAMPA. - (2005), pp. 1215033.91-1215033.95. (Intervento presentato al convegno 3rd IEEE International Conference on Advanced Learning Technologies, ICALT 2003 tenutosi a Athens, grc nel 2003) [10.1109/ICALT.2003.1215033].
InLinx for document classification, sharing and recommendation
Carbonaro A.
;
2005
Abstract
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. © 2003 IEEE.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
