Mining ontology for automatically acquiring Web user information needs Export

@article{citeulike:1367795, abstract = {It is not easy to obtain the right information from the Web for a particular Web user or a group of users due to the obstacle of automatically acquiring Web user profiles. The current techniques do not provide satisfactory structures for mining Web user profiles. This paper presents a novel approach for this problem. The objective of the approach is to automatically discover ontologies from data sets in order to build complete concept models for Web user information needs. It also proposes a method for capturing evolving patterns to refine discovered ontologies. In addition, the process of assessing relevance in ontology is established. This paper provides both theoretical and experimental evaluations for the approach. The experimental results show that all objectives we expect for the approach are achievable.}, author = {Li, Yuefeng and Zhong, Ning}, citeulike-article-id = {1367795}, citeulike-linkout-0 = {http://dx.doi.org/10.1109/TKDE.2006.1599392}, citeulike-linkout-1 = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1599392}, doi = {10.1109/TKDE.2006.1599392}, journal = {Knowledge and Data Engineering, IEEE Transactions on}, keywords = {profiling, user}, number = {4}, pages = {554--568}, posted-at = {2007-06-06 12:29:48}, priority = {5}, title = {Mining ontology for automatically acquiring Web user information needs}, url = {http://dx.doi.org/10.1109/TKDE.2006.1599392}, volume = {18}, year = {2006} }

TY - JOUR ID - citeulike:1367795 L3 - citeulike-article-id:1367795 N2 - It is not easy to obtain the right information from the Web for a particular Web user or a group of users due to the obstacle of automatically acquiring Web user profiles. The current techniques do not provide satisfactory structures for mining Web user profiles. This paper presents a novel approach for this problem. The objective of the approach is to automatically discover ontologies from data sets in order to build complete concept models for Web user information needs. It also proposes a method for capturing evolving patterns to refine discovered ontologies. In addition, the process of assessing relevance in ontology is established. This paper provides both theoretical and experimental evaluations for the approach. The experimental results show that all objectives we expect for the approach are achievable. IS - 4 JF - Knowledge and Data Engineering, IEEE Transactions on EP - 568 TI - Mining ontology for automatically acquiring Web user information needs VL - 18 SP - 554 KW - profiling KW - user AU - Li, Yuefeng AU - Zhong, Ning PY - 2006/// UR - http://dx.doi.org/10.1109/TKDE.2006.1599392 ER -