Presentation 2010/2/22
Interactive Suggestion of Related Videos by Analyzing Users' Comments Based on tf-idf Scheme
Yusuke EBATA, Hidenori KAWAMURA, Keiji SUZUKI,
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Abstract(in English) These days video sharing site such as YouTube is being popular. With that, studies using comments of videos are also paid much attention. In this study, we show the related videos for which a comment of videos was used. Specifically, we regarded all comments of one animation as one document, and calculated feature vector on every document. We used the feature vector to show as related videos by calculating the similarity with the other videos.
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Keyword(in English) YouTube / comments / feature extraction / tf-idf scheme
Paper # AI2009-43
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Conference Information
Committee AI
Conference Date 2010/2/22(1days)
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Registration To Artificial Intelligence and Knowledge-Based Processing (AI)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Interactive Suggestion of Related Videos by Analyzing Users' Comments Based on tf-idf Scheme
Sub Title (in English)
Keyword(1) YouTube
Keyword(2) comments
Keyword(3) feature extraction
Keyword(4) tf-idf scheme
1st Author's Name Yusuke EBATA
1st Author's Affiliation Graduate School of Information Science and Technology, Hokkaido University()
2nd Author's Name Hidenori KAWAMURA
2nd Author's Affiliation Graduate School of Information Science and Technology, Hokkaido University
3rd Author's Name Keiji SUZUKI
3rd Author's Affiliation Graduate School of Information Science and Technology, Hokkaido University
Date 2010/2/22
Paper # AI2009-43
Volume (vol) vol.109
Number (no) 439
Page pp.pp.-
#Pages 4
Date of Issue