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        <title>Assamese Word Sense Disambiguation using Genetic Algorithm</title>
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    <name type="personal">
        <namePart type="given">Arjun</namePart>
        <namePart type="family">Gogoi</namePart>
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    <name type="personal">
        <namePart type="given">Nomi</namePart>
        <namePart type="family">Baruah</namePart>
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    <name type="personal">
        <namePart type="given">Shikhar</namePart>
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        <namePart type="family">Sarma</namePart>
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            <title>Proceedings of the 17th International Conference on Natural Language Processing (ICON)</title>
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            <namePart type="given">Pushpak</namePart>
            <namePart type="family">Bhattacharyya</namePart>
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            <namePart type="given">Dipti</namePart>
            <namePart type="given">Misra</namePart>
            <namePart type="family">Sharma</namePart>
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        <name type="personal">
            <namePart type="given">Rajeev</namePart>
            <namePart type="family">Sangal</namePart>
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            <publisher>NLP Association of India (NLPAI)</publisher>
            <place>
                <placeTerm type="text">Indian Institute of Technology Patna, Patna, India</placeTerm>
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    <abstract>Word sense disambiguation (WSD) is a problem to determine a word according to a context in which it occurs. There are plenty amount of works done in WSD for some languages such as English, but research work on Assamese WSD remains limited. It is a more exigent task because Assamese has an intrinsic complexity in its writing structure and ambiguity, such as syntactic, semantic, and anaphoric ambiguity levels.A novel unsupervised genetic word sense disambiguation algorithm is proposed in this paper. The algorithm first uses WordNet to extract all possible senses for a given ambiguous word, then a genetic algorithm is used taking Wu-Palmer’s similarity measure as the fitness function and calculating the similarity measure for all extracted senses. The winner sense which will have the highest score declared as he winner sense.</abstract>
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        <url>https://aclanthology.org/2020.icon-main.40</url>
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        <date>2020-12</date>
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            <start>303</start>
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%0 Conference Proceedings
%T Assamese Word Sense Disambiguation using Genetic Algorithm
%A Gogoi, Arjun
%A Baruah, Nomi
%A Sarma, Shikhar Kr.
%Y Bhattacharyya, Pushpak
%Y Sharma, Dipti Misra
%Y Sangal, Rajeev
%S Proceedings of the 17th International Conference on Natural Language Processing (ICON)
%D 2020
%8 December
%I NLP Association of India (NLPAI)
%C Indian Institute of Technology Patna, Patna, India
%F gogoi-etal-2020-assamese
%X Word sense disambiguation (WSD) is a problem to determine a word according to a context in which it occurs. There are plenty amount of works done in WSD for some languages such as English, but research work on Assamese WSD remains limited. It is a more exigent task because Assamese has an intrinsic complexity in its writing structure and ambiguity, such as syntactic, semantic, and anaphoric ambiguity levels.A novel unsupervised genetic word sense disambiguation algorithm is proposed in this paper. The algorithm first uses WordNet to extract all possible senses for a given ambiguous word, then a genetic algorithm is used taking Wu-Palmer’s similarity measure as the fitness function and calculating the similarity measure for all extracted senses. The winner sense which will have the highest score declared as he winner sense.
%U https://aclanthology.org/2020.icon-main.40
%P 303-307

Markdown (Informal)

[Assamese Word Sense Disambiguation using Genetic Algorithm](https://aclanthology.org/2020.icon-main.40) (Gogoi et al., ICON 2020)

• Assamese Word Sense Disambiguation using Genetic Algorithm (Gogoi et al., ICON 2020)

ACL

• Arjun Gogoi, Nomi Baruah, and Shikhar Kr. Sarma. 2020. Assamese Word Sense Disambiguation using Genetic Algorithm. In Proceedings of the 17th International Conference on Natural Language Processing (ICON), pages 303–307, Indian Institute of Technology Patna, Patna, India. NLP Association of India (NLPAI).