DocumentCode :
2260035
Title :
Building a dictionary on constituent structure of Chinese compounds
Author :
Qiu, Likun ; Zhang, Xiaoqiao ; Mao, Ling
Author_Institution :
Inst. of Artificial Intell., Beijing City Univ., Beijing, China
fYear :
2009
fDate :
24-27 Sept. 2009
Firstpage :
1
Lastpage :
8
Abstract :
This paper presents an approach of building a contemporary Chinese dictionary on constituent structure of compounds. Manual tagging and three automatic tagging methods, including bi-direction parallel analogy, paired parallel analogy and inferring based on the consistency between form and meaning, are used. More than 40,000 words of all the 54000 bi-syllabic words in Hownet are fully or half semantically tagged by these three automatic methods. In the process of manual tagging, the difficulties and corresponding solving schemes are also presented in this paper. After manual and automatic tagging, two methods are used for checking their results. First, several heuristic rules are used on manual tagging results to mine abnormal tagging. Second, the manual and automatic tagging results are comparing with each other and the inconsistent tagging results are also considered as abnormal tagging. All abnormal tagging results are reserved for further checking.
Keywords :
data mining; dictionaries; natural language processing; text analysis; Chinese compound; Hownet; abnormal tagging; automatic tagging; bidirection parallel analogy; bisyllabic word; constituent structure; data mining; dictionary; heuristic rule; manual tagging; paired parallel analogy; semantic tagging; Artificial intelligence; Bidirectional control; Buildings; Concurrent computing; Databases; Dictionaries; Morphology; Natural languages; Speech; Tagging; Bi-direction Parallel Analogy; Grammatical Category; Grammatical Structure; Paired Parallel Analogy; Semantic Category;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Language Processing and Knowledge Engineering, 2009. NLP-KE 2009. International Conference on
Conference_Location :
Dalian
Print_ISBN :
978-1-4244-4538-7
Electronic_ISBN :
978-1-4244-4540-0
Type :
conf
DOI :
10.1109/NLPKE.2009.5313777
Filename :
5313777
Link To Document :
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