Abstract
A chemistry-focused search engine, named ChemEngine, is developed to help chemists to get chemical information more conveniently and precisely on Internet. Text Categorization is used in ChemEngine to facilitate users’ search. The semantic similarity and noisy data in chemical web pages make traditional classifier perform poorly on them. To classify chemical web pages more accurately, a new text categorization approach based on dictionary and voting is proposed and integrated into the ChemEngine.
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© 2005 Springer-Verlag Berlin Heidelberg
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Liang, C., Guo, L., Xia, Z., Li, X., Yang, Z. (2005). Dictionary-Based Voting Text Categorization in a Chemistry-Focused Search Engine. In: Ngu, A.H.H., Kitsuregawa, M., Neuhold, E.J., Chung, JY., Sheng, Q.Z. (eds) Web Information Systems Engineering – WISE 2005. WISE 2005. Lecture Notes in Computer Science, vol 3806. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11581062_59
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DOI: https://doi.org/10.1007/11581062_59
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30017-5
Online ISBN: 978-3-540-32286-3
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