Learning user profiles for personalized information dissemination

@inproceedings{citeulike:2537899, abstract = {Personalized information systems represent the recent effort of delivering information to users more effectively in the modern electronic age. This paper illustrates how a supervised adaptive resonance theory (ART) system, called fuzzy ARAM (adaptive resonance associative map), can be used to learn user profiles for personalized information dissemination. ARAM learning is online, fast, and incremental. Acquisition of new knowledge does not require re-training on previously learned cases. ARAM integrates both user-defined and system-learned knowledge in a single framework. Therefore inconsistency between the two knowledge sources will not arise. ARAM has been used to develop a personalized news system (PIN). Preliminary experiments have verified that PIN is able to provide personalized news by adapting to user's interests in an online manner and generalizing them to new information on-the-fly}, author = {Tan, Ah-Hwee and Teo, C. }, booktitle = {Neural Networks Proceedings, 1998. IEEE World Congress on Computational Intelligence. The 1998 IEEE International Joint Conference on}, citeulike-article-id = {2537899}, doi = {10.1109/IJCNN.1998.682259}, journal = {Neural Networks Proceedings, 1998. IEEE World Congress on Computational Intelligence. The 1998 IEEE International Joint Conference on}, keywords = {neural-network, personalization, user-profile}, pages = {183--188 vol.1}, posted-at = {2008-03-15 21:54:52}, priority = {2}, title = {Learning user profiles for personalized information dissemination}, url = {http://dx.doi.org/10.1109/IJCNN.1998.682259}, volume = {1}, year = {1998} }

TY - CONF ID - citeulike:2537899 L3 - citeulike-article-id:2537899 TI - Learning user profiles for personalized information dissemination T2 - Neural Networks Proceedings, 1998. IEEE World Congress on Computational Intelligence. The 1998 IEEE International Joint Conference on JF - Neural Networks Proceedings, 1998. IEEE World Congress on Computational Intelligence. The 1998 IEEE International Joint Conference on VL - 1 SP - 183 EP - 188 vol.1 N2 - Personalized information systems represent the recent effort of delivering information to users more effectively in the modern electronic age. This paper illustrates how a supervised adaptive resonance theory (ART) system, called fuzzy ARAM (adaptive resonance associative map), can be used to learn user profiles for personalized information dissemination. ARAM learning is online, fast, and incremental. Acquisition of new knowledge does not require re-training on previously learned cases. ARAM integrates both user-defined and system-learned knowledge in a single framework. Therefore inconsistency between the two knowledge sources will not arise. ARAM has been used to develop a personalized news system (PIN). Preliminary experiments have verified that PIN is able to provide personalized news by adapting to user's interests in an online manner and generalizing them to new information on-the-fly KW - neural-network KW - personalization KW - user-profile AU - Tan, Ah-Hwee AU - Teo, C PY - 1998/// UR - http://dx.doi.org/10.1109/IJCNN.1998.682259 ER -