Title :
Automatic identification of hierarchical relationship between words based on clustering
Author :
Zhou, Wei ; Du, Yuncheng ; Wang, Hongwei ; Lv, Xueqiang
Author_Institution :
Chinese Inf. Process. Res. Center, Beijing Inf. Sci. & Technol. Univ., Beijing, China
Abstract :
At present, how to use computer technology to automatically identify the semantic relations between terms, such as equivalence relationship, hierarchical relationship and associative relationship, is a key part of automatically building a thesauri, also a difficulty. In this paper, several common methods to identify the concept hierarchical relationship were described: the identification method based on co-occurrence analysis, the distribution of similarity calculation method and the method based on syntactic pattern matching, proposed a combination method of co-occurrence statistics and distribution of similarity calculation to identify the concept hierarchical relationships between words, and proved by experiments that the method is feasible and effective.
Keywords :
pattern clustering; statistical analysis; text analysis; thesauri; word processing; associative relationship; automatic identification; computer technology; concept hierarchical relationship; cooccurrence analysis; cooccurrence statistics; equivalence relationship; semantic relations; similarity calculation method distribution; syntactic pattern matching; thesauri; Algorithm design and analysis; Clustering algorithms; Context; Natural languages; Semantics; Thesauri; Vectors; automatic identification of hierarchical relationship; clustering; co-occurrence analysis; the associated concept of space; thesauri;
Conference_Titel :
Transportation, Mechanical, and Electrical Engineering (TMEE), 2011 International Conference on
Conference_Location :
Changchun
Print_ISBN :
978-1-4577-1700-0
DOI :
10.1109/TMEE.2011.6199512