Concept Extraction Methods for Agricultural Product–Related Texts Based on Natural Language Processing Techniques: A Case Study of Online Vegetable-Product Reviews
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- Takezaki Akane
- National Agricultural Research Center
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- Oura Yuji
- National Agricultural Research Center Tokyo University of Agriculture
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- Kono Yoshinobu
- National Agricultural Research Center
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- Kiura Takuji
- National Agricultural Research Center
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- Hayashi Takeshi
- National Agricultural Research Center
Bibliographic Information
- Other Title
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- 自然言語処理を利用した農産物関連テキストからの概念抽出―野菜商品レビューを対象事例として―
Abstract
In this paper, we evaluated adaptation problems to general natural language processing (NLP) when applied to online vegetable- product reviews. Some keywords (nouns, verbs, and adjectives) extracted from vegetable- product reviews did not adequately represent their concepts because of generally low accuracy related to chunking, synonyms, a lack of applicable target nouns, and negative concepts. We proposed concept extraction methods based on NLP to solve these problems, including (1) morpheme analysis by reference to an additional custom dictionary; (2) combination of the verb “する” with the preceding noun; (3) acquisition of negative meaning, conversion of the auxiliary verb “ぬ” to the verb “無い” or the suffix “ない”, combination of the prefix “無”, “不”, “低”, “未”, or “非” with the following noun or adjective, and a combination of the suffix “ない” with the preceding adjective or verb; (4) synonym substitution; and (5) identification of target nouns that have related adjectives.
Journal
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- Agricultural Information Research
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Agricultural Information Research 25 (1), 47-58, 2016
Japanese Society of Agricultural Informatics
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Keywords
Details 詳細情報について
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- CRID
- 1390001204460451584
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- NII Article ID
- 130005141438
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- ISSN
- 18815219
- 09169482
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- Text Lang
- ja
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- Data Source
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- JaLC
- Crossref
- CiNii Articles
- KAKEN
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- Abstract License Flag
- Disallowed