Discover Linguistic Patterns in Parsed Corpus with Frequent Subrtree Mining

Author

Wang, Bo ; Zhao, Tiejun ; Yang, Muyun ; Li, Sheng

Author_Institution

Sch. of Comput. Sci. & Technol., Harbin Inst. of Technol., Harbin, China

fYear

2010

fDate

9-10 Jan. 2010

Firstpage

86

Lastpage

89

Abstract

Recognition of special linguistic patterns in a certain language is very helpful for many NLP applications such as information extraction, machine translation and parsing. State-of-the-arts syntax parsers are based on given grammar. The used grammar is context free and cannot discover complex patterns which contain multiple linguistic units. We propose an unsupervised method to automatically discover the complex linguistic patterns from a classically parsed corpus. A specialized and efficient algorithm is applied to mine the frequent subtrees in the forest and the found subtrees are formalized as the linguistic patterns. The approach is validated on the Penn Chinese Treebank with found linguistic patterns.

Keywords

context-free grammars; data mining; natural language processing; trees (mathematics); NLP applications; complex linguistic patterns; complex pattern discovery; context free grammar; discover linguistic patterns; frequent subrtree mining; information extraction; machine translation; parsed corpus; parsing; syntax parsers; Application software; Computer science; Data mining; Humans; Natural language processing; Natural languages; Neural networks; Pattern recognition; linguistic patterns; parsing; subtree mining;

fLanguage

English

Publisher

ieee

Conference_Titel

Knowledge Discovery and Data Mining, 2010. WKDD '10. Third International Conference on

Conference_Location

Phuket

Print_ISBN

978-1-4244-5397-9

Electronic_ISBN

978-1-4244-5398-6

Type

conf

DOI

10.1109/WKDD.2010.9

Filename

5432720