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PSO-Tagger: A New Biologically Inspired Approach to the Part-of-Speech Tagging Problem
2013
anapaulasilva13a
In this paper we present an approach to the part-of-speech tagging problem based on particle swarm optimization. The part-of-speech tagging is a key input feature for several other natural language processing tasks, like phrase chunking and named entity recognition. A tagger is a system that should receive a text, made of sentences, and, as output, should return the same text, but with each of its words associated with the correct part-of-speech tag. The task is not straightforward, since a large percentage of words have more than one possible part-of-speech tag, and the right choice is determined by the part-of-speech tags of the surrounding words, which can also have more than one possible tag. In this work we investigate the possibility of using a particle swarm optimization algorithm to solve the part-of-speech tagging problem supported by a set of disambiguation rules. The results we obtained on two different corpora are amongst the best ones published for those corpora.
Book chapter
Ana Paula Silva, Arlindo Silva, Irene Rodrigues
Marco Tomassini
Adaptive and Natural Computing Algorithms
Lecture Notes in Computer Science Volume , 2013,
Springer
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7824
90-99
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Ana Paula Silva and Arlindo Silva and Irene Rodrigues, PSO-Tagger: A New Biologically Inspired Approach to the Part-of-Speech Tagging Problem, in: Marco Tomassini (eds), Adaptive and Natural Computing Algorithms, Lecture Notes in Computer Science Volume , 2013,, Springer, Vol. 7824, Pag. 90-99, 2013.
Ana Paula Silva, Arlindo Silva and <a href="/people/members/view.php?code=032b48c4371cf1d1523215c3f02c42de" class="author">Irene Rodrigues</a>, <b>PSO-Tagger: A New Biologically Inspired Approach to the Part-of-Speech Tagging Problem</b>, in: Marco Tomassini (eds), <u>Adaptive and Natural Computing Algorithms</u>, Lecture Notes in Computer Science Volume , 2013,, <a href="http://www.springer.com" title="Link to external entity..." target="_blank" class="publisher">Springer</a>, Vol. 7824, Pag. 90-99, 2013.
@incollection {anapaulasilva13a, author = {Ana Paula Silva and Arlindo Silva and Irene Rodrigues}, editor = {Marco Tomassini}, title = {PSO-Tagger: A New Biologically Inspired Approach to the Part-of-Speech Tagging Problem}, booktitle = {Adaptive and Natural Computing Algorithms}, series = {Lecture Notes in Computer Science Volume , 2013,}, publisher = {Springer}, volume = {7824}, pages = {90-99}, abstract = {In this paper we present an approach to the part-of-speech tagging problem based on particle swarm optimization. The part-of-speech tagging is a key input feature for several other natural language processing tasks, like phrase chunking and named entity recognition. A tagger is a system that should receive a text, made of sentences, and, as output, should return the same text, but with each of its words associated with the correct part-of-speech tag. The task is not straightforward, since a large percentage of words have more than one possible part-of-speech tag, and the right choice is determined by the part-of-speech tags of the surrounding words, which can also have more than one possible tag. In this work we investigate the possibility of using a particle swarm optimization algorithm to solve the part-of-speech tagging problem supported by a set of disambiguation rules. The results we obtained on two different corpora are amongst the best ones published for those corpora.}, year = {2013}, }
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