TY - GEN
T1 - What is the basic semantic unit of chinese language? A computational approach based on topic models
AU - Zhao, Qi
AU - Qin, Zengchang
AU - Wan, Tao
PY - 2011
Y1 - 2011
N2 - Chinese language has been generally regarded as a Subject-Verb -Object (SVO) language and the basic semantic unit is the Chinese word that is usually consisted by two or more Chinese characters. However, word-centered structure of Chinese language has been controversial in linguistics. Some recent research in computational linguistics in Chinese language suggests that the character-based models perform better than the word-based models in some applications such word segmentation. In this paper, the word-based topic models and the character-based models are tested for modeling Chinese language, respectively. By empirical studies, we demonstrated the effectiveness of using Chinese characters as the basic semantic units. These two models have close performance in text classifications while the character-based model has a better quality in language modeling and a much smaller vocabulary. By testing on a bilingual corpus, three independent topic models based on Chinese words, Chinese characters and English words are trained and compared to each other. we verify the capability of topic models in modeling semantics by experiments across Chinese and English. The classification accuracy can also be boosted up by aggregating the classification results from the three independent topic models.
AB - Chinese language has been generally regarded as a Subject-Verb -Object (SVO) language and the basic semantic unit is the Chinese word that is usually consisted by two or more Chinese characters. However, word-centered structure of Chinese language has been controversial in linguistics. Some recent research in computational linguistics in Chinese language suggests that the character-based models perform better than the word-based models in some applications such word segmentation. In this paper, the word-based topic models and the character-based models are tested for modeling Chinese language, respectively. By empirical studies, we demonstrated the effectiveness of using Chinese characters as the basic semantic units. These two models have close performance in text classifications while the character-based model has a better quality in language modeling and a much smaller vocabulary. By testing on a bilingual corpus, three independent topic models based on Chinese words, Chinese characters and English words are trained and compared to each other. we verify the capability of topic models in modeling semantics by experiments across Chinese and English. The classification accuracy can also be boosted up by aggregating the classification results from the three independent topic models.
UR - https://www.scopus.com/pages/publications/80054023437
U2 - 10.1007/978-3-642-23211-4_9
DO - 10.1007/978-3-642-23211-4_9
M3 - 会议稿件
AN - SCOPUS:80054023437
SN - 9783642232107
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 143
EP - 157
BT - The Mathematics of Language - 12th Biennial Conference, MOL 12, Proceedings
T2 - 12th Meeting on Mathematics of Language, MOL 12
Y2 - 6 September 2011 through 8 September 2011
ER -