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Focused crawling for retrieving chemical information
Xia, Z. J.; Guo, L.; Liang, C. Y.; Li, X. X.; Yang, Z. Y.
Conference Name2nd International Workshop on Hybrid Artificial Intelligence Systems
Source PublicationADVANCES IN SOFT COMPUTING Volume: 44 Pages: 433-438
Conference DateNOV, 2007
Conference PlaceUniv Salamanca, Salamanca, SPAIN
PublisherSpringer-Verlag Berlin
AbstractThe exponential growth of resources available in the Web has made it important to develop instruments to perform search efficiently. This paper proposes an approach for chemical information discovery by using focused crawling. The comparison of combination using various feature representations and classifier algorithms to implement focused crawlers was carried out. Latent Semantic Indexing (LSI) and Mutual Information (MI) were used to extract features from documents, while Naive Bayes (NB) and Support Vector Machines (SVM) were the selected algorithms to compute content relevance score. It was found that the combination of LSI and SVM provided the best solution.
Indexed ByISTP
Document Type会议论文
Recommended Citation
GB/T 7714
Xia, Z. J.,Guo, L.,Liang, C. Y.,et al. Focused crawling for retrieving chemical information[C]:Springer-Verlag Berlin,2007:433-438.
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