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Spatiality and Its Semantic Consequence of the Quantitative Expression “一CCN” in Mandarin Chinese Read chapter Read first chapter

2020 | OriginalPaper | Chapter

Tibetan Sentence Similarity Evaluation Based on Vectorized Representation Techniques

Authors : Zhou Maoxian, Cizhen Jiacuo, Cai Rangjia

Published in: Chinese Lexical Semantics

Publisher: Springer International Publishing

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Abstract

Sentence similarity evaluation is an essential subject among the researching fields of Natural Language Processing (NLP), however, Tibetan related research on this subject is fairly inactive and has rarely drawn attention. In this work, we proposed an approach by leveraging vectorized representation techniques to tackle this problem by implementing two methods, namely, Euclidean distance evaluation and Jaccard similarity evaluation. Experiments indicated the performance of presented methods is satisfactory.

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previous chapter Automatic Recognition of Chinese Separable Words Based on CRFs
next chapter An Easier and Efficient Framework to Annotate Semantic Roles: Evidence from the Chinese AMR Corpus
Footnotes
Literature
1.
Li, B., Liu, T., Qin, B., Li, S.: Chinese sentence similarity calculation based on semantic dependence. Comput. Appl. Res. 20(12), 15–17 (2003). (in Chinese)
2.
Zhou, W.: Research on the calculation method of Chinese sentence similarity and its application. Master thesis, Henan University, (2005). (in Chinese)
3.
Anjian, C.: Research on the algorithm of Tibetan sentence similarity. Chin. J. Inf. 25(4), 2–6 (2011). (in Chinese)
4.
Yan, M.: Research on the calculation method of Tibetan text similarity based on segmentation fusion. Master thesis, Northwest University for Nationalities (2016). (in Chinese)
5.
Li, F., Hou, J., Zeng, R., Ling, C.: Research on multi-character sentence similarity calculation method of fusion word vector. Comput. Sci. Explor. 11(4), 608–618 (2017). (in Chinese)
6.
Hinton, G.E.: Learning distributed representations of concepts. In: Proceedings of the Eighth Annual Conference of the Cognitive Science Society, vol. 1, p. 12 (1986)
7.
Mikolov, T., Chen, K., Corrado, G., Dean, J.: Efficient estimation of word representations in vector space. arXiv preprint arXiv:​1301.​3781 (2013)
Metadata
Title
Tibetan Sentence Similarity Evaluation Based on Vectorized Representation Techniques
Authors
Zhou Maoxian
Cizhen Jiacuo
Cai Rangjia
Copyright Year
2020
Book
Chinese Lexical Semantics

Print ISBN: 978-3-030-38188-2

Electronic ISBN: 978-3-030-38189-9

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-3-030-38189-9_48

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