Title :
Cooperation of evolutionary and statistical PoS-tagging
Author :
Forsati, Rana ; Shamsfard, Mehrnoush
Author_Institution :
NLP Res. Lab., Shahid Beheshti Univ., Tehran, Iran
Abstract :
Part-of-Speech tagging which refers to assignment of syntactic categories to words is a fundamental task in Natural Language Processing (NLP). This paper presents a novel algorithm based on Bee Colony Optimization (BCO) for POS tagging. Experimental results indicate that the proposed algorithm outperforms the other evolutionary-based and tested classical Part-of-Speech -tagging approaches in terms of average accuracy.
Keywords :
evolutionary computation; natural language processing; optimisation; BCO; NLP; bee colony optimization; evolutionary PoS-tagging; evolutionary-based part-of-speech-tagging approaches; natural language processing; statistical PoS-tagging; tested classical part-of-speech-tagging approaches; Accuracy; Algorithm design and analysis; Context; Natural language processing; Optimization; Signal processing algorithms; Tagging; bee colony optimization; natural language processing; part of speech tagging;
Conference_Titel :
Artificial Intelligence and Signal Processing (AISP), 2012 16th CSI International Symposium on
Conference_Location :
Shiraz, Fars
Print_ISBN :
978-1-4673-1478-7
DOI :
10.1109/AISP.2012.6313789
