TY  - JOUR
T1  - TopicSearch - Personalized Web Clustering Engine Using Semantic Query Expansion, Memetic Algorithms and Intelligent Agents
JO  - Polibits (Journal on Research and Development in Computer Science and Engineering)
VL  - 47
SP  - 31
EP  - 45
PY  - 2013/6//
T2  - 
AU  - Cobos, Carlos
AU  - Mendoza, Martha
AU  - Leon, Elizabeth
AU  - Manic, Milos
AU  - Herrera-Viedma, Enrique
SN  - 1870-9044
DO  - 
UR  - http://polibits.gelbukh.com/2013_47
KW  - Web Document Clustering
KW  - Intelligent Agents
KW  - Query Expansion
KW  - WordNet
KW  - Memetic Algorithm
KW  - User Profile
AB  - As resources become more and more available on the Web, so the difficulties associated with finding the desired information increase. Intelligent agents can assist users in this task since they can search, filter and organize information on behalf of their users. Web document clustering techniques can also help users to find pages that meet their information requirements. This paper presents a personalized web document clustering called TopicSearch. TopicSearch introduces a novel inverse document frequency function to improve the query expansion process, a new memetic algorithm for web document clustering, and frequent phrases approach for defining cluster labels. Each user query is handled by an agent who coordinates several tasks including query expansion, search results acquisition, preprocessing of search results, cluster construction and labeling, and visualization. These tasks are performed by specialized agents whose execution can be parallelized in certain instances. The model was successfully tested on fifty DMOZ datasets. The results demonstrated improved precision and recall over traditional algorithms (k-means, Bisecting k-means, STC y Lingo). In addition, the presented model was evaluated by a group of twenty users with 90% being in favor of the model.
ER  -