دانلود مقاله انگلیسی رایگان:توکاری چند حسه از طریق فرایند تفسیر کلمه حس - 2019
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  • Multi-sense embeddings through a word sense disambiguation process Multi-sense embeddings through a word sense disambiguation process
    Multi-sense embeddings through a word sense disambiguation process

    سال انتشار:

    2019


    عنوان انگلیسی مقاله:

    Multi-sense embeddings through a word sense disambiguation process


    ترجمه فارسی عنوان مقاله:

    توکاری چند حسه از طریق فرایند تفسیر کلمه حس


    منبع:

    Sciencedirect - Elsevier - Expert Systems With Applications, 136 (2019) 288-303: doi:10:1016/j:eswa:2019:06:026


    نویسنده:

    Terry Ruas a , ∗, William Grosky a , Akiko Aizawa b


    چکیده انگلیسی:

    Natural Language Understanding has seen an increasing number of publications in the last few years, especially after robust word embeddings models became prominent, when they proved themselves able to capture and represent semantic relationships from massive amounts of data. Nevertheless, traditional models often fall short in intrinsic issues of linguistics, such as polysemy and homonymy. Any expert system that makes use of natural language in its core, can be affected by a weak semantic representation of text, resulting in inaccurate outcomes based on poor decisions. To mitigate such issues, we propose a novel approach called Most Suitable Sense Annotation (MSSA) , that disambiguates and annotates each word by its specific sense, considering the semantic effects of its context. Our approach brings three main contributions to the semantic representation scenario: (i) an unsupervised technique that disambiguates and annotates words by their senses, (ii) a multi-sense embeddings model that can be extended to any traditional word embeddings algorithm, and (iii) a recurrent methodology that allows our models to be re-used and their representations refined. We test our approach on six different benchmarks for the word similarity task, showing that our approach can produce state-of-the-art results and outperforms several more complex state-of-the-art systems.
    Keywords: Multi-sense | embeddings Natural language processing | Word similarity | Synset


    سطح: متوسط
    تعداد صفحات فایل pdf انگلیسی: 16
    حجم فایل: 685 کیلوبایت

    قیمت: رایگان


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