IJCIRISSN 1996-1065 [Online]
ISSN 1818-1139 [PRINT]

Volume 2 (2) 2008

Title:	Towards Domain Independent Named Entity Recognition
Authors:	Fredrick E.K. & Baryamureeba Venansius *, Guy De Pauw
Published:	©IJCIR Vol2 (2) 2008, PP. 84-95
Language:	English

Abstract:
Named entity recognition is a preprocessing tool to many natural language processing tasks, such as text summarization, speech translation, and document ategorization. Many systems for named entity recognition have been developed over the past years with substantial success save for the problem of being domain specific and making it difficult to use the different systems across domains. This work attempts to surmount the problem by proposing the use of domain independent features with a aximum entropy model and a multiobjective genetic algorithm (MOGA) to select the best features. The methods used in this work are backed up by experiments of which the classifications are evaluated using two diverse domains. Conclusions are finally drawn and the outlook for future work is considered. View full Article

Categories and Subject Descriptors: I.2.7 [Artificial Intelligence]: Natural Language Processing— language parsing and understanding; I.5.2 [Pattern Recognition]: Design Methodology— Feature evaluation and selection General Terms: Computer Science, Language Processing, Machine Learning Additional Key Words and Phrases: domain independent, named entity recognition, multiobjective genetic algorithm