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Bag of Visual Words - n_hidekeyã®æ—¥è¨˜
Bag of visual words (BoVW)ã¯ã€ä¸€èˆ¬ç‰©ä½“èªè˜ã«ãŠã„ã¦ç¾åœ¨æœ€ã‚‚åºƒãæ™®åŠã—ã¦ã„ã‚‹ç”»åƒç‰¹å¾´è¡¨ç¾ã§ã€ç”»åƒä¸ã®å¤šæ•°ã®å±€æ‰€ç‰¹å¾´ã‚’ãƒ™ã‚¯ãƒˆãƒ«é‡ååŒ–ã—ãƒ’ã‚¹ãƒˆã‚°ãƒ©ãƒ ã«ã—ãŸã‚‚ã®ã§ã™ã€‚æœ€è¿‘ã¯OpenCVãªã©ã®ãƒ„ãƒ¼ãƒ«ã®æ™®åŠã«ã‚ˆã‚Šä½¿ã„ã‚„ã™ããªã£ã¦ãã¾ã—ãŸãŒã€å®Ÿéš›ã«ä½¿ã£ã¦ã¿ã‚ˆã†ã¨ã™ã‚‹ã¨ç´°ã‹ã„éƒ¨åˆ†ã§ã¤ã¾ã¥ãã“ã¨ã‚‚å¤šã„ã®ã§ã¯ãªã„ã§ã—ã‚‡ã†ã‹ã€‚æœ€æ–°ã®ç ”ç©¶ã§ã¯èªè˜ç²¾åº¦ãŒé£›èºçš„ã«å‘ä¸Šã—ã¦ã„ã¾ã™ãŒã€å±€æ‰€ç‰¹å¾´æŠ½å‡ºãªã©ã®ç´°ã‹ã„ãƒŽã‚¦ãƒã‚¦ã®è“„ç©ã«ã‚ˆã‚‹éƒ¨åˆ†ã‚‚ã‹ãªã‚Šå¤§ãã„ã¨æ€ã„ã¾ã™ã€‚ ï¼ˆãã®ã‚ˆã†ãªéƒ¨åˆ†ã¯å¦è¡“çš„ãªæ–°è¦æ€§ã¯ä½Žã„ãŸã‚ã€è«–æ–‡ã§ã¯ã•ã‚‰ã‚Šã¨æ›¸ã„ã¦ã‚ã‚‹ã“ã¨ãŒå¤šã„ã®ã§ã™ãŒï¼‰ ä»¥ä¸‹ã€è‡ªåˆ†ãŒæŠŠæ¡ã—ã¦ã„ã‚‹ãƒŽã‚¦ãƒã‚¦ã‚’ã¾ã¨ã‚ã¦ã¿ãŸã„ã¨æ€ã„ã¾ã™ã€‚ãŸã ã—ã€ç§è‡ªèº«ã®çµŒé¨“ã‚„ä¸»è¦³ã«åŸºã¥ãã‚‚ã®ã§ã‚ã‚Šã€çµ¶å¯¾çš„ãªã‚‚ã®ã§ã¯ãªã„ã“ã¨ã«ã”æ³¨æ„ãã ã•ã„ã€‚ ã¾ãŸã€BoVWã«ã¤ã„ã¦åŸºæœ¬çš„ãªçŸ¥è˜ãŒã‚ã‚‹ã“ã¨ã‚’å‰æã¨ã—ã¦ã„ã¾ã™ã€‚ ç”»åƒã‚µã‚¤ã‚º ã¾ãšã€ãã‚‚ãã‚‚ç”»åƒã¯ã©
fuba 2011/11/21
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A Survey on Music Data Mining
Mining Association Patterns between Music and Video Clips in Professional MTV (Journal: Advances in Multimedia Modeling '09)Â [PDF]Â [Bibtex] Use a dual-wing harmonium model to learn and represent the underlying association patterns between music and video clips in professional MTV.
fuba 2011/10/03
music

survey

mining
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éŽåŽ»10å¹´é–“ã®Computer Scienceç³»è«–æ–‡ã§è¢«å¼•ç”¨æ•°ãƒˆãƒƒãƒ—10ã‚’ä½œã£ã¦ã¿ãŸ - æƒ…å ±ç§‘å¦å±‹ã•ã‚“ã‚’ç›®æŒ‡ã™äººã®ãƒ¡ãƒ¢ï¼ˆFC2ãƒ–ãƒã‚°ç‰ˆï¼‰
ä½•ã‹ã®ã‚„ã‚Šæ–¹ã‚„ã€å•é¡Œã®è§£æ±ºæ–¹æ³•ã‚’ã©ã‚“ã©ã‚“ãƒ¡ãƒ¢ã™ã‚‹ãƒ–ãƒã‚°ã€‚ãã‚“ãªå¤§å¦é™¢ç”Ÿã®æ´»å‹•ã€Œã‚ãƒ£ãƒƒã‚·ãƒ¥ã€ã«èª°ã‹ãŒãƒ’ãƒƒãƒˆã—ã¦ãã‚Œã‚‹ã“ã¨ã‚’ç¥ˆã£ã¦ã€‚ 2000å¹´ä»¥é™ã®è«–æ–‡ã«é™å®šã—ã¦ã€ CSç³»è«–æ–‡ã®è¢«å¼•ç”¨æ•°ãƒ©ãƒ³ã‚ãƒ³ã‚°ã‚’ä½œã£ã¦åˆ†æžã—ã¦ã¿ãŸã€‚ ã“ã®ä½œæ¥ã‚’é€šã˜ã¦äºˆæƒ³ä»¥ä¸Šã«å¾—ã‚‹ã‚‚ã®ãŒã‚ã£ãŸã€‚ ãƒ©ãƒ³ã‚ãƒ³ã‚°ã®ä½œã‚Šæ–¹ CiteSeerXãŒå…¬é–‹ã—ã¦ã„ã‚‹ã€ŒMost Cited Computer Science ArticlesÂ (2010/9/14)ã€ã‚’å…ƒãƒ‡ãƒ¼ã‚¿ã«æŽ¡ç”¨ã—ãŸã€‚ ã“ã“ã‹ã‚‰2000å¹´ä»¥é™ã®æ–‡ç« ã«é™å®šã—ãŸå¾Œã€ãƒãƒ³ãƒ‰ãƒ–ãƒƒã‚¯ã‚„é›‘èªŒè¨˜äº‹ãªã©ã‚’å–ã‚Šé™¤ã„ã¦è«–æ–‡ã ã‘ã®ãƒ©ãƒ³ã‚ãƒ³ã‚°ã‚’ä½œæˆã—ãŸã€‚ è¢«å¼•ç”¨æ•°ã¯æ™‚é–“ãŒçµŒã¤ã»ã©å¢—ãˆã‚‹ä¸€æ–¹ãªã®ã§ã€2000å¹´ãƒ»2001å¹´ã‚ãŸã‚Šã®è«–æ–‡ãŒæœ‰åˆ©ã§ã‚ã‚‹ã“ã¨ã«æ³¨æ„ã™ã‚‹å¿…è¦ãŒã‚ã‚‹ã€‚ ãŸã ã—ã€ã“ã®ã“ã¨ãŒã‹ãˆã£ã¦å¾—ã‚‹ã‚‚ã®ã‚’å¢—ã‚„ã—ã¦ãã‚ŒãŸã€‚ ã‚¢ãƒ–ã‚¹ãƒˆãƒ©ã‚¯ãƒˆã‚’ãƒã‚§ãƒƒã‚¯ è‰¯ã„æ©Ÿä¼šã§ã‚ã‚‹ã®ã§ã€ å„è«–æ–‡ã®æ¦‚è¦ã‚„çµè«–ã‚’ãƒã‚§ãƒƒã‚¯
fuba 2011/09/21
cs

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ç‰©ä½“èªè˜ã®ãŸã‚ã®å±€æ‰€ç‰¹å¾´é‡ SIFTã¨æœ€è¿‘ã®ã‚¢ãƒ—ãƒãƒ¼ãƒ
ç‰©ä½“èªè˜ã®ãŸã‚ã®å±€æ‰€ç‰¹å¾´é‡ SIFTã¨æœ€è¿‘ã®ã‚¢ãƒ—ãƒãƒ¼ãƒ http://www.vision.cs.chubu.ac.jp/SIFT/ è—¤å‰ å¼˜äº˜ ä¸éƒ¨å¤§å¦å·¥å¦éƒ¨æƒ…å ±å·¥å¦ç§‘ æ¦‚è¦ 1. SIFT(Scale-Invariant Feature Transf orm) 2. SIFTã‚¢ãƒ—ãƒãƒ¼ãƒã®é«˜ç²¾åº¦åŒ– - PCA-SIFT - GLOH(Gradient Location and Orientation) 3. SIFTã‚¢ãƒ—ãƒãƒ¼ãƒã®é«˜é€ŸåŒ– - SURF(Speeded Up Robust Features) 4. å¦ç¿’ã‚’ç”¨ã„ãŸé«˜é€ŸåŒ– - Randomized Trees 5. SIFTã¨ä¸€èˆ¬ç‰©ä½“èªè˜(ç”»åƒåˆ†é¡ž) 1. SIFT(Scale-Invariant Feature Transf orm) ã‚¹ãƒ†ãƒ¬ã‚ªç”»åƒ Related Work å›žè»¢ãƒ»ã‚¹ã‚±ãƒ¼ãƒ«å¤‰åŒ– ç…§æ˜Žå¤‰åŒ–ç‰ã«é ‘å¥ ç‰¹å¾´ç‚¹æ¤œå‡º ã‚¹ã‚±ãƒ¼
fuba 2009/10/19
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WWW2009ã®ã‚µãƒ¼ãƒ™ã‚¤@æƒ…å ±çˆ†ç™ºã‚ãƒƒã‚¯ã‚ªãƒ• - è±Šç”°æ£å²ã®SLã¨ã¯é–¢ä¿‚ã”ã–ã„ã¾ã›ã‚“(2009-05-14)
_ [å¦ä¼š] WWW2009ã®ã‚µãƒ¼ãƒ™ã‚¤@æƒ…å ±çˆ†ç™ºã‚ãƒƒã‚¯ã‚ªãƒ• æƒ…å ±çˆ†ç™ºã®ã‚ãƒƒã‚¯ã‚ªãƒ•ãƒŸãƒ¼ãƒ†ã‚£ãƒ³ã‚°ã§WWW2009ã®15åˆ†ã‚µãƒ¼ãƒ™ã‚¤ã¨ã„ã†ç„¡è¬€ãªè©¦ã¿ã‚’ã‚„ã‚‰ã•ã‚ŒãŸã®ã§ã€ç™ºè¡¨è³‡æ–™ã‚’ä»¥ä¸‹ã«ç½®ã„ã¦ã¿ã¾ã™ã€‚ã‚ãƒ¼ãƒŽãƒ¼ãƒˆ2æœ¬ã€è«–æ–‡æ•°ã®å¤šã„3ã‚»ãƒƒã‚·ãƒ§ãƒ³ã‹ã‚‰æµè¡Œã‚Šã‚’æŠœãå‡ºã™ãŸã‚ã€ã‚¿ã‚¤ãƒˆãƒ«ã€ã‚¢ãƒ–ã‚¹ãƒˆã‚’ã‚¿ã‚°ã‚¯ãƒ©ã‚¦ãƒ‰åŒ–ã—ã¦ãƒˆãƒ¬ãƒ³ãƒ‰è«–æ–‡ã‚’ãƒªã‚¹ãƒˆã‚¢ãƒƒãƒ—ã€‚ã„ãã¤ã‹ã®è«–æ–‡ã«ã¤ã„ã¦ã¡ã‚‡ã£ã¨ã ã‘ç´¹ä»‹ã€‚ã¨è¨€ã†å½¢ã«ã—ã¾ã—ãŸã€‚å…¨ä½“çš„ã«ã€Yahoo!, MSã®è«–æ–‡ãŒå¤šãã€ã¡ã‚‡ã£ã¨ãŠã‚‚ã—ã‚ç›®ã®ã‚¢ã‚¤ãƒ‡ã‚¢ã‚’ã€æ¤œç´¢ã‚¨ãƒ³ã‚¸ãƒ³ä¼šç¤¾ã®å®Ÿãƒ‡ãƒ¼ã‚¿ã§å®Ÿé¨“ã—ã¦ã—ã£ã‹ã‚Šè©•ä¾¡ã™ã‚‹ã¨ã„ã†è«–æ–‡ãŒå¤šãé€šã£ã¦ã„ã‚‹å°è±¡ã§ã™ã€‚å¤§å¦ã®æ•™å“¡ãŒä¼æ¥ã‚’å…¼å‹™ã—ã¦ã„ãŸã‚Šã€ã‚¤ãƒ³ã‚¿ãƒ¼ãƒ³ã®å¦ç”ŸãŒæ¤œç´¢ã‚¨ãƒ³ã‚¸ãƒ³ä¼šç¤¾ã«è¡Œã£ã¦ä»•äº‹ã—ãŸã®ã‚’ã¾ã¨ã‚ã¦ã„ãŸã‚Šã¨ã€ä¼æ¥ã¨å¤§å¦ã®é€£æºãŒã†ã¾ãã„ã£ã¦ã„ã‚‹ã¨ã„ã†ã“ã¨ã§ã—ã‚‡ã†ãã€‚ WWW2009survey.pdf
fuba 2009/05/14
mining

www

survey
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Mining Meaning from Wikipedia
Wikipedia is a goldmine of information; not just for its many readers, but also for the growing community of researchers who recognize it as a resource of exceptional scale and utility. It represents a vast investment of manual effort and judgment: a huge, constantly evolving tapestry of concepts and relations that is being applied to a host of tasks. This article provides a comprehensive descript
fuba 2009/05/12
survey

wikipedia

mining
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Lectures: Web Engineering
è¬›ç¾©æƒ…å ±/ã‚¦ã‚§ãƒ–å·¥å¦ ã‚¦ã‚§ãƒ–å·¥å¦ è±Šç”°æ£å²(ç”Ÿç”£ç ”) é›»åæƒ…å ±å¦å°‚æ”», 2007 å†¬, æœˆ 14:45-16:15 è¬›ç¾©å†…å®¹ 10/01 ã‚¤ãƒ³ãƒˆãƒãƒ€ã‚¯ã‚·ãƒ§ãƒ³ è¬›ç¾©è³‡æ–™ Anna Patterson. Why Writing Your Own Search Engine is Hard. ACM Queue vol.2 no.2, 2004 10/15 å¤§è¦æ¨¡æ¤œç´¢ã‚¨ãƒ³ã‚¸ãƒ³ã®ä»•çµ„ã¿ Sergey Brin and Lawrence Page. The Anatomy of a Large-Scale Hypertextual Web Search Engine. WWW7, 1998 11/05 ãƒšãƒ¼ã‚¸ãƒ©ãƒ³ã‚¯ Page, Lawrence; Brin, Sergey; Motwani, Rajeev; Winograd, Terry. The PageRank Citation Ranking
fuba 2007/12/02
science

web

survey
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ã‚½ãƒ¼ã‚·ãƒ£ãƒ«ãƒãƒƒãƒˆãƒ¯ãƒ¼ã‚¯ã‚µã‚¤ãƒˆã®ç ”ç©¶è€…ã€ç ”ç©¶è«–æ–‡ãƒªã‚¹ãƒˆ - YAMDASç¾æ›´æ–°å±¥æ´
apophenia: Research on Social Network Sites ã“ã®ãƒ–ãƒã‚°ä¸»ã§ã‚ã‚‹ danah boydï¼ˆWikipediaï¼‰ã‚’ã¯ã˜ã‚ã¨ã—ã¦ã€ã‚½ãƒ¼ã‚·ãƒ£ãƒ«ãƒãƒƒãƒˆãƒ¯ãƒ¼ã‚¯ã«é–¢ã™ã‚‹ä¸»è¦ãªç ”ç©¶è€…ã¨ãã®è«–æ–‡ã®ãƒªãƒ³ã‚¯é›†ã«ãªã£ã¦ã„ã‚‹ã€‚ æ¬§ç±³ã® SNS ã«é–¢ã™ã‚‹å¦è¡“çš„ãªè©•ä¾¡ã‚„çªã£è¾¼ã‚“ã ç ”ç©¶ã‚’çŸ¥ã‚ŠãŸã„äººã¯èªã‚€ã¨ã‚ˆã„ã ã‚ã†ã€‚
fuba 2006/08/29
academic

sns

paper

survey
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Research on Social Network Sites | danah boyd | apophenia
UPDATE: This page is out-of-date. An updated list can be found here: Research on Social Network Sites Thank you! I want to track down everyone who is actively doing research on social network sites. (Clarification: iâ€™m looking for folks that are publishing in peer-reviewed spaces, not just researching for their company or blog.) Nicole Ellison and i are plotting to bring ways to bring everyone tog
fuba 2006/08/29
academic

sns

paper

survey
ãƒªãƒ³ã‚¯
æœ¬ä¼šè°1æ—¥ç›®, ãƒ¬ã‚»ãƒ—ã‚·ãƒ§ãƒ³ã¨æ™©å¾¡é£¯ - è±Šç”°æ£å²ã®SLã¨ã¯é–¢ä¿‚ã”ã–ã„ã¾ã›ã‚“(2006-05-24)
_ [WWW2006] æœ¬ä¼šè°1æ—¥ç›® ä»Šæ—¥ã‹ã‚‰æœ¬ä¼šè°ã€‚ã‚ªãƒ¼ãƒ—ãƒ‹ãƒ³ã‚°ã§ã¯Sir Tim Berners-Leeä»–3åãŒãƒ‘ãƒãƒ«è¨Žè«–ã§ã‚»ãƒžãƒ³ãƒ†ã‚£ãƒƒã‚¯ã‚»ãƒžãƒ³ãƒ†ã‚£ãƒƒã‚¯ã¨ãŠã£ã—ã‚ƒã£ã¦ã„ãŸã€‚å‚åŠ ã—ãŸã‚»ãƒƒã‚·ãƒ§ãƒ³ã¯ã€Fighting Search Spamã€Browsersã€Web Miningã€‚Web Miningã‚»ãƒƒã‚·ãƒ§ãƒ³ã§ã¯è‡ªåˆ†ã®è«–æ–‡ç™ºè¡¨ã€‚åçœç‚¹å¤šã—ã€‚ä»¥ä¸‹ã€å¾Œã§èªã‚‚ã†ã¨æ€ã£ã¦ã„ã‚‹è«–æ–‡ã¨ã€ç§ã®è«–æ–‡ã®ç´¹ä»‹ã€‚ Topical TrustRank: Using Topicality to Combat Web Spam PageRankã‚’Topic Sensitive PageRankã«ã—ãŸã‚ˆã†ã«ã€TrustRankã‚’TopicalTrustRankã«ã—ãŸã€‚ã®ã‹ï¼Ÿè‰¯ãã‚ã‹ã‚‰ãªã‹ã£ãŸã®ã§å¾Œã§èªã‚€ã€‚ Detecting Spam Web Pages through Content Analysis ãƒšãƒ¼ã‚¸ã‚³ãƒ³ãƒ†ãƒ³
fuba 2006/05/31
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fuba 2005/08/23
tech

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