A Genetic Algorithm Based Approach for Hindi Word Sense Disambiguation
| Autor: | Gunjan Pareek, Anidhya Athaiya, Deepa Modi |
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| Rok vydání: | 2018 |
| Předmět: |
Hindi
Computer science business.industry WordNet Context (language use) Meaning (non-linguistic) computer.software_genre language.human_language Expression (mathematics) Feature (machine learning) language Applications of artificial intelligence Artificial intelligence business computer Natural language processing Word (computer architecture) |
| Zdroj: | 2018 3rd International Conference on Communication and Electronics Systems (ICCES). |
| Popis: | Word Sense Disambiguation (WSD) is the procedure of selecting precise sense or meaning for a word in a given context. Word sense disambiguation goes about as an establishment to different AI applications as data mining, information recovery, and machine interpretation. The issue solicits to figure out which sense from the polysemous word is appropriate in a given context. Previously a few methodologies have been proposed for WSD in English, German and so forth, however, work on WSD in Hindi is limited. In this work, a genetic algorithm based approach is presented for Hindi WSD. The feature of dynamic setting window is used which contains left and right expression of a vague word. The cardinal supposition of this approach is that the target word must have a common topic in its neighborhood. For finding all possible senses of an ambiguous word, WordNet created by IIT Bombay is used. |
| Databáze: | OpenAIRE |
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