Title :
A Service Retrieval Assistance Mechanism Based on Association Mining
Author :
Bin Tang ; Leqiu Qian ; Yunjiao Xue
Author_Institution :
Dept. of Comput. Sci. & Eng., Fudan Univ., Shanghai
fDate :
Aug. 30 2006-Sept. 1 2006
Abstract :
During the process of service retrieval, it´s often difficult for users to give exact retrieval requirements because users are not familiar with the complex description mechanism of services. This limits the function of ontology service models and leads to lower completion, precision, efficiency and easiness of service retrieval. It is urgent to have an efficient method to help the users. The paper introduces a self-adaptive learning algorithm based on association mining theory in data mining field to learn from the retrieval history and assist users in giving high quality retrieval requirements. The experiment results show the effectivity of the proposed algorithm
Keywords :
Internet; data mining; information retrieval; ontologies (artificial intelligence); unsupervised learning; Web service; association mining; data mining; ontology; self-adaptive learning algorithm; service retrieval assistance mechanism; Computer science; Data mining; History; Information retrieval; Mobile computing; Plugs; Production; Quality of service; Time measurement; Web services;
Conference_Titel :
Innovative Computing, Information and Control, 2006. ICICIC '06. First International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7695-2616-0
DOI :
10.1109/ICICIC.2006.220