Abstract
This paper presents an automatic method to extract the agent and patient relation of the short-texts. With the aid of the “HowNet”, the real agent and patient relation in the real short-texts are determined via the common feature and the “sememe-tree” structure. Moreover, the strength of the relations can be calculated by using the length in the “sememe-tree”. Furthermore, the extracted word pairs are used for the classification of short-texts. The experiments demonstrate the validity of the proposed approach in extracting the agent and patient relation from short-texts. And the relations are beneficial for improving the performance of short-text classification.
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© 2011 Springer-Verlag Berlin Heidelberg
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Fan, X., Wei, D. (2011). A Method of Agent and Patient Relation Acquisition for Short-Text Classification. In: Shen, G., Huang, X. (eds) Advanced Research on Computer Science and Information Engineering. CSIE 2011. Communications in Computer and Information Science, vol 153. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21411-0_5
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DOI: https://doi.org/10.1007/978-3-642-21411-0_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-21410-3
Online ISBN: 978-3-642-21411-0
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