Title :
Named Entity Relation Extraction Based on Multiple Features
Author_Institution :
Inner Mongolia Univ. of Finance & Econ., Hohhot, China
Abstract :
For the limited availability of established Mongolian named entity dictionary, with the increase of the new terminology and network vocabulary, Mongolian named entity dictionary was not able to update in time. This paper puts forward a method of named entity recognition, which based on a combination of multiple features and CRF. The method of named entity recognition proposed in this paper firstly cluster the entities that never appear in the repository with the method of hierarchical converged clustering, then carry through the normal words recognition and adjust the results of feature base.
Keywords :
feature extraction; natural language processing; pattern clustering; CRF; Mongolian named entity dictionary; entity clustering; hierarchical converged clustering; multiple features; named entity recognition; named entity relation extraction; normal words recognition; Context; Dictionaries; Feature extraction; Organizations; Speech recognition; Text recognition; Training; Feature; Named Entity Recognition; Part-of-speech tagging;
Conference_Titel :
Advanced Information Networking and Applications Workshops (WAINA), 2015 IEEE 29th International Conference on
Conference_Location :
Gwangiu
Print_ISBN :
978-1-4799-1774-7
DOI :
10.1109/WAINA.2015.14