WORD SENSE DISAMBIGUATION USING FUZZY SEMANTIC-BASED STRING SIMILARITY MODEL
Sentences are the language of human communication. This communication medium is so fluid that words and meaning can have many interpretations by readers. Besides, a document that consists of thousands of sentences would be tough for the reader to understand the content. In this case, computer power...
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| Format: | Article |
| Language: | English |
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UiTM Press
2018-12-01
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| Series: | Malaysian Journal of Computing |
| Subjects: |
| _version_ | 1797454181531910144 |
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| author | Amir Abd-Rashid, Shuzlina Abdul-Rahman, Nor Nadiah Yusof, Azlinah Mohamed |
| author_facet | Amir Abd-Rashid, Shuzlina Abdul-Rahman, Nor Nadiah Yusof, Azlinah Mohamed |
| author_sort | Amir Abd-Rashid, Shuzlina Abdul-Rahman, Nor Nadiah Yusof, Azlinah Mohamed |
| collection | DOAJ |
| description | Sentences are the language of human communication. This communication medium is so fluid that words and meaning can have many interpretations by readers. Besides, a document that consists of thousands of sentences would be tough for the reader to understand the content. In this case, computer power is required to analyse the gigantic batch size of the text. However, there are several arguments that actively discuss regarding the output generated by a computer toward the meaning of the passage in terms of accuracy. One of the reasons for this issue is the existing of the ambiguous word with multiple meanings in a sentence. The passage might be incorrectly translated due to wrong sense selection during the early phase of sentence translation. Translating sentence in this paper means either the sentence has a negative or positive meaning. Thus, this research discusses on how to disambiguate the term in a sentence by referring to the Wordnet repository by proposing the use of fuzzy semantic-based similarity model. The proposed model promising to return a good result for detecting the similarity of two sentences that has been proven in the past research. At the end of this paper, preliminary result which shows the flow of how the proposed framework working is discussed. |
| first_indexed | 2024-03-09T15:33:34Z |
| format | Article |
| id | doaj.art-da1b4b74a3aa4a7b8f588ca230400c32 |
| institution | Directory Open Access Journal |
| issn | 2600-8238 |
| language | English |
| last_indexed | 2024-03-09T15:33:34Z |
| publishDate | 2018-12-01 |
| publisher | UiTM Press |
| record_format | Article |
| series | Malaysian Journal of Computing |
| spelling | doaj.art-da1b4b74a3aa4a7b8f588ca230400c322023-11-26T11:19:14ZengUiTM PressMalaysian Journal of Computing2600-82382018-12-0132154161https://doi.org/10.24191/mjoc.v3i2.4890WORD SENSE DISAMBIGUATION USING FUZZY SEMANTIC-BASED STRING SIMILARITY MODELAmir Abd-Rashid, Shuzlina Abdul-Rahman, Nor Nadiah Yusof, Azlinah MohamedSentences are the language of human communication. This communication medium is so fluid that words and meaning can have many interpretations by readers. Besides, a document that consists of thousands of sentences would be tough for the reader to understand the content. In this case, computer power is required to analyse the gigantic batch size of the text. However, there are several arguments that actively discuss regarding the output generated by a computer toward the meaning of the passage in terms of accuracy. One of the reasons for this issue is the existing of the ambiguous word with multiple meanings in a sentence. The passage might be incorrectly translated due to wrong sense selection during the early phase of sentence translation. Translating sentence in this paper means either the sentence has a negative or positive meaning. Thus, this research discusses on how to disambiguate the term in a sentence by referring to the Wordnet repository by proposing the use of fuzzy semantic-based similarity model. The proposed model promising to return a good result for detecting the similarity of two sentences that has been proven in the past research. At the end of this paper, preliminary result which shows the flow of how the proposed framework working is discussed.disambiguityfuzzysentiwordnetwordnet |
| spellingShingle | Amir Abd-Rashid, Shuzlina Abdul-Rahman, Nor Nadiah Yusof, Azlinah Mohamed WORD SENSE DISAMBIGUATION USING FUZZY SEMANTIC-BASED STRING SIMILARITY MODEL Malaysian Journal of Computing disambiguity fuzzy sentiwordnet wordnet |
| title | WORD SENSE DISAMBIGUATION USING FUZZY SEMANTIC-BASED STRING SIMILARITY MODEL |
| title_full | WORD SENSE DISAMBIGUATION USING FUZZY SEMANTIC-BASED STRING SIMILARITY MODEL |
| title_fullStr | WORD SENSE DISAMBIGUATION USING FUZZY SEMANTIC-BASED STRING SIMILARITY MODEL |
| title_full_unstemmed | WORD SENSE DISAMBIGUATION USING FUZZY SEMANTIC-BASED STRING SIMILARITY MODEL |
| title_short | WORD SENSE DISAMBIGUATION USING FUZZY SEMANTIC-BASED STRING SIMILARITY MODEL |
| title_sort | word sense disambiguation using fuzzy semantic based string similarity model |
| topic | disambiguity fuzzy sentiwordnet wordnet |
| work_keys_str_mv | AT amirabdrashidshuzlinaabdulrahmannornadiahyusofazlinahmohamed wordsensedisambiguationusingfuzzysemanticbasedstringsimilaritymodel |