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Photo identity tag suggestion using only social network context on large-scale web services
Recently, uploading photos and adding identity tags on social network services are prevalent. Although some researchers have considered leveraging context to facilitate the process of tagging, these approaches still rely mainly on face recognition techniques that use visual features of photos. Howev...
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creator | Chi-Yao Tseng Ming-Syan Chen |
description | Recently, uploading photos and adding identity tags on social network services are prevalent. Although some researchers have considered leveraging context to facilitate the process of tagging, these approaches still rely mainly on face recognition techniques that use visual features of photos. However, since the computational and storage costs of these approaches are generally high, they cannot be directly applicable to large-scale web services. To resolve this problem, we explore using only social network context to generate the top-k list of photo identity tag suggestion. The proposed method is based on various co-occurrence contexts that are related to the question of who may appear in this photo. An efficient ranking algorithm is designed to satisfy the real-time needs of this application. We utilize public album data of 400 volunteers from Facebook to verify that our approach can efficiently provide accurate suggestions with less additional storage requirement. |
doi_str_mv | 10.1109/ICME.2011.6012061 |
format | conference_proceeding |
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Although some researchers have considered leveraging context to facilitate the process of tagging, these approaches still rely mainly on face recognition techniques that use visual features of photos. However, since the computational and storage costs of these approaches are generally high, they cannot be directly applicable to large-scale web services. To resolve this problem, we explore using only social network context to generate the top-k list of photo identity tag suggestion. The proposed method is based on various co-occurrence contexts that are related to the question of who may appear in this photo. An efficient ranking algorithm is designed to satisfy the real-time needs of this application. We utilize public album data of 400 volunteers from Facebook to verify that our approach can efficiently provide accurate suggestions with less additional storage requirement.</description><identifier>ISSN: 1945-7871</identifier><identifier>ISBN: 1612843484</identifier><identifier>ISBN: 9781612843483</identifier><identifier>EISSN: 1945-788X</identifier><identifier>EISBN: 1612843506</identifier><identifier>EISBN: 9781612843490</identifier><identifier>EISBN: 9781612843506</identifier><identifier>EISBN: 1612843492</identifier><identifier>DOI: 10.1109/ICME.2011.6012061</identifier><language>eng</language><publisher>IEEE</publisher><subject>Algorithm design and analysis ; Context ; Face ; Face recognition ; large-scale web services ; Photo identity tag suggestion ; real-time suggestion ; social network context ; Social network services ; Tagging ; Web services</subject><ispartof>2011 IEEE International Conference on Multimedia and Expo, 2011, p.1-4</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/6012061$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,27925,54555,54920,54932</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/6012061$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Chi-Yao Tseng</creatorcontrib><creatorcontrib>Ming-Syan Chen</creatorcontrib><title>Photo identity tag suggestion using only social network context on large-scale web services</title><title>2011 IEEE International Conference on Multimedia and Expo</title><addtitle>ICME</addtitle><description>Recently, uploading photos and adding identity tags on social network services are prevalent. Although some researchers have considered leveraging context to facilitate the process of tagging, these approaches still rely mainly on face recognition techniques that use visual features of photos. However, since the computational and storage costs of these approaches are generally high, they cannot be directly applicable to large-scale web services. To resolve this problem, we explore using only social network context to generate the top-k list of photo identity tag suggestion. The proposed method is based on various co-occurrence contexts that are related to the question of who may appear in this photo. An efficient ranking algorithm is designed to satisfy the real-time needs of this application. We utilize public album data of 400 volunteers from Facebook to verify that our approach can efficiently provide accurate suggestions with less additional storage requirement.</description><subject>Algorithm design and analysis</subject><subject>Context</subject><subject>Face</subject><subject>Face recognition</subject><subject>large-scale web services</subject><subject>Photo identity tag suggestion</subject><subject>real-time suggestion</subject><subject>social network context</subject><subject>Social network services</subject><subject>Tagging</subject><subject>Web services</subject><issn>1945-7871</issn><issn>1945-788X</issn><isbn>1612843484</isbn><isbn>9781612843483</isbn><isbn>1612843506</isbn><isbn>9781612843490</isbn><isbn>9781612843506</isbn><isbn>1612843492</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2011</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNo90MtKAzEYBeB4A2vtA4ibvMDU_DO5zVJKq4WKLhQEFyWT_DNGx4lMUuu8vQVLz-YsPjiLQ8gVsCkAK2-Ws4f5NGcAU8kgZxKOyAVIyDUvBJPHZAQlF5nS-vXkAFzz0wMoOCeTGD_YLorzkhUj8vb0HlKg3mGXfBpoMg2Nm6bBmHzo6Cb6rqGhawcag_WmpR2mbeg_qQ1dwt-0M9qavsEsWtMi3WJFI_Y_3mK8JGe1aSNO9j0mL4v58-w-Wz3eLWe3q8yDEilDh9ZVTiurchBM1DV3SqEUjmuUPAdVOeVEycBUla0hl0Jbi87YshYGVDEm1_-7HhHX373_Mv2w3p9U_AFGP1lN</recordid><startdate>201107</startdate><enddate>201107</enddate><creator>Chi-Yao Tseng</creator><creator>Ming-Syan Chen</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201107</creationdate><title>Photo identity tag suggestion using only social network context on large-scale web services</title><author>Chi-Yao Tseng ; Ming-Syan Chen</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-edecdbd87c721505ff4d77e65d48e64217bd7d5901abbcf12658ccedac9f5a173</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Algorithm design and analysis</topic><topic>Context</topic><topic>Face</topic><topic>Face recognition</topic><topic>large-scale web services</topic><topic>Photo identity tag suggestion</topic><topic>real-time suggestion</topic><topic>social network context</topic><topic>Social network services</topic><topic>Tagging</topic><topic>Web services</topic><toplevel>online_resources</toplevel><creatorcontrib>Chi-Yao Tseng</creatorcontrib><creatorcontrib>Ming-Syan Chen</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Xplore</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Chi-Yao Tseng</au><au>Ming-Syan Chen</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Photo identity tag suggestion using only social network context on large-scale web services</atitle><btitle>2011 IEEE International Conference on Multimedia and Expo</btitle><stitle>ICME</stitle><date>2011-07</date><risdate>2011</risdate><spage>1</spage><epage>4</epage><pages>1-4</pages><issn>1945-7871</issn><eissn>1945-788X</eissn><isbn>1612843484</isbn><isbn>9781612843483</isbn><eisbn>1612843506</eisbn><eisbn>9781612843490</eisbn><eisbn>9781612843506</eisbn><eisbn>1612843492</eisbn><abstract>Recently, uploading photos and adding identity tags on social network services are prevalent. Although some researchers have considered leveraging context to facilitate the process of tagging, these approaches still rely mainly on face recognition techniques that use visual features of photos. However, since the computational and storage costs of these approaches are generally high, they cannot be directly applicable to large-scale web services. To resolve this problem, we explore using only social network context to generate the top-k list of photo identity tag suggestion. The proposed method is based on various co-occurrence contexts that are related to the question of who may appear in this photo. An efficient ranking algorithm is designed to satisfy the real-time needs of this application. We utilize public album data of 400 volunteers from Facebook to verify that our approach can efficiently provide accurate suggestions with less additional storage requirement.</abstract><pub>IEEE</pub><doi>10.1109/ICME.2011.6012061</doi><tpages>4</tpages></addata></record> |
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ispartof | 2011 IEEE International Conference on Multimedia and Expo, 2011, p.1-4 |
issn | 1945-7871 1945-788X |
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source | IEEE Xplore All Conference Series |
subjects | Algorithm design and analysis Context Face Face recognition large-scale web services Photo identity tag suggestion real-time suggestion social network context Social network services Tagging Web services |
title | Photo identity tag suggestion using only social network context on large-scale web services |
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