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  1. A500 情報学部/情報学研究科・情報文化学部・情報科学研究科
  2. A500a 雑誌掲載論文
  3. 学術雑誌

Improved Hashtag Recommendation Algorithm Determining Appropriate Hashtags for Words with Different Meanings

http://hdl.handle.net/2237/0002011895
http://hdl.handle.net/2237/0002011895
8690fd57-167f-44b9-a948-e8f517516c0f
名前 / ファイル ライセンス アクション
main.pdf main.pdf (4.1 MB)
アイテムタイプ itemtype_ver1(1)
公開日 2025-01-21
タイトル
タイトル Improved Hashtag Recommendation Algorithm Determining Appropriate Hashtags for Words with Different Meanings
言語 en
著者 Kamino, Etsutaro

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en Kamino, Etsutaro

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Kita, Eisuke

× Kita, Eisuke

en Kita, Eisuke

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アクセス権
アクセス権 open access
アクセス権URI http://purl.org/coar/access_right/c_abf2
権利
権利情報 This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/s12626-024-00173-3
言語 en
内容記述
内容記述タイプ Abstract
内容記述 In image-posting social networking services, such as Instagram, recommendation of appropriate hashtags for posts is vital. In the existing methods, a hashtag is searched using the names of object labels included in images added to posts as hashtags, and a relevance prediction model is applied to hashtags that appear most frequently among those attached to posts obtained from the search. Hashtags that are considered highly relevant to the post are then recommended to the user. However, it is difficult to recommend adequate hashtags relevant to a post containing a label that refers to different objects, such as “mouse,” which can refer to a “computer input device” and an “animal.” In this study, we developed algorithms (Algorithms 1 and 2) that employ additional labels related to object labels in posts to solve this problem. As additional labels, Algorithm 1 uses the other labels in the same object category in the Microsoft Common Objects in Context (COCO) image database, and Algorithm 2 uses words translated into six other languages. We also developed Algorithm 3, which is a hybrid of Algorithms 1 and 2. Based on user questionnaires, the hashtags suggested by Algorithms 1 and 2 are highly relevant to the posts: compared to an existing algorithm, the relevance of the hashtags improved by 18% and 64%, respectively.
言語 en
内容記述
内容記述タイプ Other
内容記述 Online Published: 17 September 2024
言語 en
出版者
出版者 Springer
言語 en
言語
言語 eng
資源タイプ
資源タイプresource http://purl.org/coar/resource_type/c_6501
タイプ journal article
出版タイプ
出版タイプ AM
出版タイプResource http://purl.org/coar/version/c_ab4af688f83e57aa
関連情報
関連タイプ isVersionOf
識別子タイプ DOI
関連識別子 https://doi.org/10.1007/s12626-024-00173-3
収録物識別子
収録物識別子タイプ PISSN
収録物識別子 2523-3173
書誌情報 en : The Review of Socionetwork Strategies

巻 19, p. 1-17, 発行日 2025-04
ファイル公開日
日付 2025-09-17
日付タイプ Available
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