Title :
Recognizing location names from Chinese texts based on Max-Margin Markov Network
Author :
Li, Lishuang ; Ding, Zhuoye ; Huang, Degen
Author_Institution :
Dalian Univ. of Technol., Dalian
Abstract :
This paper presents a novel method of recognizing location names from Chinese texts based on max-margin Markov Network (M3Net) owing to its ability to exploit very high dimensional feature spaces (using the kernel trick) while at the same time dealing with structured data compared with Support Vector Machine (SVM) and conditional random fields (CRFs). In our model, the character itself, character-based part-of-speech (POS) tag, the information whether a character appears in the location name characteristic word table and context information are extracted as the features. The F-measure is up to 90.57% based on 1-order M3Net which is better than that based on either SVM or CRFs in open test on MSRA dataset.
Keywords :
Markov processes; character recognition; support vector machines; text analysis; Chinese text; F-measure; character-based part-of-speech tag; conditional random field; context information extraction; location name characteristic word table; location names recognition; max-margin Markov network; structured data; support vector machine; Information retrieval; Libraries; Markov random fields; Natural languages; Optical computing; Performance evaluation; Relational databases; Spatial databases; Testing; Text recognition; CRFs; M3Net; SVM; named entity recognition;
Conference_Titel :
Natural Language Processing and Knowledge Engineering, 2008. NLP-KE '08. International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-4515-8
Electronic_ISBN :
978-1-4244-2780-2
DOI :
10.1109/NLPKE.2008.4906752