Automated user modeling for personalized digital libraries Export

@article{citeulike:892552, abstract = {Digital libraries (DLs) have become one of the most typical ways of accessing any kind of digitalized information. Due to this key role, users welcome any improvements on the services they receive from DLs. One trend used to improve digital services is through personalization. Up to now, the most common approach for personalization in DLs has been user driven. Nevertheless, the design of efficient personalized services has to be done, at least in part, in an automatic way. In this context, machine learning techniques automate the process of constructing user models. This paper proposes a new approach to construct DLs that satisfy a user's necessity for information: Adaptive DLs, libraries that automatically learn user preferences and goals and personalize their interaction using this information.}, author = {Frias-Martinez, E. and Magoulas, G. and Chen, S. and Macredie, R.}, citeulike-article-id = {892552}, citeulike-linkout-0 = {http://dx.doi.org/10.1016/j.ijinfomgt.2006.02.006}, citeulike-linkout-1 = {http://www.sciencedirect.com/science/article/B6VB4-4JX9VDP-2/2/59bcc6a481cc73ca5dd6e49e5e96b523}, doi = {10.1016/j.ijinfomgt.2006.02.006}, journal = {International Journal of Information Management}, keywords = {digital-library, personalization, user-modeling}, month = {June}, number = {3}, pages = {234--248}, posted-at = {2007-06-20 16:31:17}, priority = {0}, title = {Automated user modeling for personalized digital libraries}, url = {http://dx.doi.org/10.1016/j.ijinfomgt.2006.02.006}, volume = {26}, year = {2006} }

TY - JOUR ID - citeulike:892552 L3 - citeulike-article-id:892552 N2 - Digital libraries (DLs) have become one of the most typical ways of accessing any kind of digitalized information. Due to this key role, users welcome any improvements on the services they receive from DLs. One trend used to improve digital services is through personalization. Up to now, the most common approach for personalization in DLs has been user driven. Nevertheless, the design of efficient personalized services has to be done, at least in part, in an automatic way. In this context, machine learning techniques automate the process of constructing user models. This paper proposes a new approach to construct DLs that satisfy a user's necessity for information: Adaptive DLs, libraries that automatically learn user preferences and goals and personalize their interaction using this information. IS - 3 JF - International Journal of Information Management EP - 248 TI - Automated user modeling for personalized digital libraries VL - 26 SP - 234 KW - digital-library KW - personalization KW - user-modeling AU - Frias-Martinez, E AU - Magoulas, G AU - Chen, S AU - Macredie, R PY - 2006/06// UR - http://dx.doi.org/10.1016/j.ijinfomgt.2006.02.006 ER -