Commentary-based video categorization and concept discovery

Janice Kwan Wai Leung; Chun Hung Li; Ting Keung Ip

doi:10.1145/1651437.1651446

Commentary-based video categorization and concept discovery

Janice Kwan Wai Leung
, Chun Hung Li
, Ting Keung Ip

Department of Computer Science

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

3 Citations (Scopus)

Abstract

Social network contents are not limited to text but also multimedia. Dailymotion, YouTube, and MySpace are examples of successful sites which allow users to share videos among themselves. Due to the huge amount of videos, grouping videos with similar contents together can help users to search videos more efficiently. Unlike the traditional approach to group videos into some predefined categories, we propose a novel comment-based matrix factorization technique to categorize videos and generate concept words to facilitate searching and indexing. Since the categorization is learnt from users feedback, it can accurately represent the user sentiment on the videos. Experiments conducted by using empirical data collected from YouTube shows the effectiveness of our proposed methodologies.

Original language	English
Title of host publication	SWSM '09: Proceedings of the 2nd ACM workshop on Social web search and mining
Publisher	Association for Computing Machinery (ACM)
Pages	49-56
Number of pages	8
ISBN (Print)	9781605588063
DOIs	https://doi.org/10.1145/1651437.1651446
Publication status	Published - 2 Nov 2009
Event	2nd ACM Workshop on Social Web Search and Mining, SWSM'09, Co-located with the 18th ACM International Conference on Information and Knowledge Management, CIKM 2009 - Hong Kong, China Duration: 2 Nov 2009 → 6 Nov 2009

Publication series

Name	Proceedings of the ACM workshop on Social web search and mining
Publisher	Association for Computing Machinery

Conference

Conference	2nd ACM Workshop on Social Web Search and Mining, SWSM'09, Co-located with the 18th ACM International Conference on Information and Knowledge Management, CIKM 2009
Country/Territory	China
City	Hong Kong
Period	2/11/09 → 6/11/09

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

User-Defined Keywords

Clustering
Comments
Social networds
Video sharing sites
YouTube

Access to Document

10.1145/1651437.1651446

Cite this

@inproceedings{c63b21ed44ca4f68a5a30c290e019c61,

title = "Commentary-based video categorization and concept discovery",

abstract = "Social network contents are not limited to text but also multimedia. Dailymotion, YouTube, and MySpace are examples of successful sites which allow users to share videos among themselves. Due to the huge amount of videos, grouping videos with similar contents together can help users to search videos more efficiently. Unlike the traditional approach to group videos into some predefined categories, we propose a novel comment-based matrix factorization technique to categorize videos and generate concept words to facilitate searching and indexing. Since the categorization is learnt from users feedback, it can accurately represent the user sentiment on the videos. Experiments conducted by using empirical data collected from YouTube shows the effectiveness of our proposed methodologies.",

keywords = "Clustering, Comments, Social networds, Video sharing sites, YouTube",

author = "Leung, \{Janice Kwan Wai\} and Li, \{Chun Hung\} and Ip, \{Ting Keung\}",

note = "Publisher copyright: Copyright 2009 ACM; 2nd ACM Workshop on Social Web Search and Mining, SWSM'09, Co-located with the 18th ACM International Conference on Information and Knowledge Management, CIKM 2009 ; Conference date: 02-11-2009 Through 06-11-2009",

year = "2009",

month = nov,

day = "2",

doi = "10.1145/1651437.1651446",

language = "English",

isbn = "9781605588063",

series = "Proceedings of the ACM workshop on Social web search and mining",

publisher = "Association for Computing Machinery (ACM)",

pages = "49--56",

booktitle = "SWSM '09: Proceedings of the 2nd ACM workshop on Social web search and mining",

address = "United States",

}

Leung, JKW, Li, CH & Ip, TK 2009, Commentary-based video categorization and concept discovery. in SWSM '09: Proceedings of the 2nd ACM workshop on Social web search and mining. Proceedings of the ACM workshop on Social web search and mining, Association for Computing Machinery (ACM), pp. 49-56, 2nd ACM Workshop on Social Web Search and Mining, SWSM'09, Co-located with the 18th ACM International Conference on Information and Knowledge Management, CIKM 2009, Hong Kong, China, 2/11/09. https://doi.org/10.1145/1651437.1651446

Commentary-based video categorization and concept discovery. / Leung, Janice Kwan Wai; Li, Chun Hung; Ip, Ting Keung.
SWSM '09: Proceedings of the 2nd ACM workshop on Social web search and mining. Association for Computing Machinery (ACM), 2009. p. 49-56 (Proceedings of the ACM workshop on Social web search and mining).

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

TY - GEN

T1 - Commentary-based video categorization and concept discovery

AU - Leung, Janice Kwan Wai

AU - Li, Chun Hung

AU - Ip, Ting Keung

PY - 2009/11/2

Y1 - 2009/11/2

N2 - Social network contents are not limited to text but also multimedia. Dailymotion, YouTube, and MySpace are examples of successful sites which allow users to share videos among themselves. Due to the huge amount of videos, grouping videos with similar contents together can help users to search videos more efficiently. Unlike the traditional approach to group videos into some predefined categories, we propose a novel comment-based matrix factorization technique to categorize videos and generate concept words to facilitate searching and indexing. Since the categorization is learnt from users feedback, it can accurately represent the user sentiment on the videos. Experiments conducted by using empirical data collected from YouTube shows the effectiveness of our proposed methodologies.

AB - Social network contents are not limited to text but also multimedia. Dailymotion, YouTube, and MySpace are examples of successful sites which allow users to share videos among themselves. Due to the huge amount of videos, grouping videos with similar contents together can help users to search videos more efficiently. Unlike the traditional approach to group videos into some predefined categories, we propose a novel comment-based matrix factorization technique to categorize videos and generate concept words to facilitate searching and indexing. Since the categorization is learnt from users feedback, it can accurately represent the user sentiment on the videos. Experiments conducted by using empirical data collected from YouTube shows the effectiveness of our proposed methodologies.

KW - Clustering

KW - Comments

KW - Social networds

KW - Video sharing sites

KW - YouTube

UR - https://www.scopus.com/pages/publications/74049139534

U2 - 10.1145/1651437.1651446

DO - 10.1145/1651437.1651446

M3 - Conference proceeding

AN - SCOPUS:74049139534

SN - 9781605588063

T3 - Proceedings of the ACM workshop on Social web search and mining

SP - 49

EP - 56

BT - SWSM '09: Proceedings of the 2nd ACM workshop on Social web search and mining

PB - Association for Computing Machinery (ACM)

T2 - 2nd ACM Workshop on Social Web Search and Mining, SWSM'09, Co-located with the 18th ACM International Conference on Information and Knowledge Management, CIKM 2009

Y2 - 2 November 2009 through 6 November 2009

ER -

Commentary-based video categorization and concept discovery

Abstract

Publication series

Conference

UN SDGs

User-Defined Keywords

Access to Document

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Cite this