Title :
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
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;
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
DOI :
10.1109/WKDD.2010.9
