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sotarok 2009/12/10
ç§»è»¢ã—ã¦ãŸï¼Ž from: http://b.hatena.ne.jp/entry/staff.aist.go.jp/toru-nakata/sotsuron.html

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sotarok 2009/12/04
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SOSP 2009é©å½“ã¾ã¨ã‚ - moratorium
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sotarok 2009/08/24
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Managing Gigabyteså‹‰å¼·ä¼šã§è»¢ç½®ã‚¤ãƒ³ãƒ‡ãƒƒã‚¯ã‚¹ã®åœ§ç¸®ã®è©±ãŒå‡ºãŸã®ã§å®Ÿéš›ã«åœ§ç¸®ã‚’è¡Œã£ãŸå ´åˆã«ã©ã‚Œãã‚‰ã„ã®ã‚µã‚¤ã‚ºã«ãªã‚‹ã‹ã‚’è¨ˆæ¸¬ã—ã¦ã¿ãŸã€‚ åˆ©ç”¨ã—ãŸãƒ‡ãƒ¼ã‚¿ã¯è‹±èªžç‰ˆWikidiaã®å…¨è¨˜äº‹ã§ æ–‡æ›¸æ•° 2,872,589 å˜èªžæ•° 2,735,620 è»¢ç½®ã‚¤ãƒ³ãƒ‡ãƒƒã‚¯ã‚¹ã®ãƒã‚¤ãƒ³ã‚¿ã®æ•° 397,603,176 ãã‚‰ã„ã®ã‚µã‚¤ã‚ºã®ãƒ‡ãƒ¼ã‚¿ã§ã™ã€‚ ç„¡åœ§ç¸®ã®è»¢ç½®ã‚¤ãƒ³ãƒ‡ãƒƒã‚¯ã‚¹ã®ãƒ•ã‚©ãƒ¼ãƒžãƒƒãƒˆã¯ å˜èªžID,æ–‡æ›¸æ•°,æ–‡æ›¸1,....æ–‡æ›¸N, å˜èªžID,...ã§å„é …ç›®4byteã¨ãªã£ã¦ãŠã‚Šã€1.5Gãã‚‰ã„ã®ã‚µã‚¤ã‚ºã«ãªã£ã¦ã„ã¾ã™ã€‚ ã“ã‚Œã«å¯¾ã—ã¦å„åœ§ç¸®ã‚¢ãƒ«ã‚´ãƒªã‚ºãƒ ã‚’é©ç”¨ã—ãŸçµæžœã¯ ã‚¢ãƒ«ã‚´ãƒªã‚ºãƒ ç„¡åœ§ç¸® Variable Byte Code unaryç¬¦å· Î³ç¬¦å· Î´ç¬¦å· Rice Coding pforDelta(ä»®) ã‚µã‚¤ã‚º 1537MB 497MB 239475MB 474MB 407MB 367MB 455MB
sotarok 2009/08/06
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sotarok 2009/08/04
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sotarok 2009/08/03
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The Anatomy of a Search Engine
Computer Science Department, Stanford University, Stanford, CA 94305 In this paper, we present Google, a prototype of a large-scale search engine which makes heavy use of the structure present in hypertext. Google is designed to crawl and index the Web efficiently and produce much more satisfying search results than existing systems. The prototype with a full text and hyperlink database of at leas
sotarok 2009/07/30
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google

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ã‚¯ãƒ©ã‚¹ã‚¿ãƒªãƒ³ã‚° (ã‚¯ãƒ©ã‚¹ã‚¿ãƒ¼åˆ†æž) - Toshihiro Kamishima
ã‚¯ãƒ©ã‚¹ã‚¿ãƒªãƒ³ã‚° (clustering) ã¨ã¯ï¼Œåˆ†é¡žå¯¾è±¡ã®é›†åˆã‚’ï¼Œå†…çš„çµåˆ (internal cohesion) ã¨å¤–çš„åˆ†é›¢ (external isolation) ãŒé”æˆã•ã‚Œã‚‹ã‚ˆã†ãªéƒ¨åˆ†é›†åˆã«åˆ†å‰²ã™ã‚‹ã“ã¨ [Everitt 93, å¤§æ©‹ 85] ã§ã™ï¼Žçµ±è¨ˆè§£æžã‚„å¤šå¤‰é‡è§£æžã®åˆ†é‡Žã§ã¯ã‚¯ãƒ©ã‚¹ã‚¿ãƒ¼åˆ†æž (cluster analysis) ã¨ã‚‚å‘¼ã°ã‚Œï¼ŒåŸºæœ¬çš„ãªãƒ‡ãƒ¼ã‚¿è§£æžæ‰‹æ³•ã¨ã—ã¦ãƒ‡ãƒ¼ã‚¿ãƒžã‚¤ãƒ‹ãƒ³ã‚°ã§ã‚‚é »ç¹ã«åˆ©ç”¨ã•ã‚Œã¦ã„ã¾ã™ï¼Ž åˆ†å‰²å¾Œã®å„éƒ¨åˆ†é›†åˆã¯ã‚¯ãƒ©ã‚¹ã‚¿ã¨å‘¼ã°ã‚Œã¾ã™ï¼Žåˆ†å‰²ã®æ–¹æ³•ã«ã‚‚å¹¾ã¤ã‹ã®ç¨®é¡žãŒã‚ã‚Šï¼Œå…¨ã¦ã®åˆ†é¡žå¯¾è±¡ãŒã¡ã‚‡ã†ã©ä¸€ã¤ã ã‘ã®ã‚¯ãƒ©ã‚¹ã‚¿ã®è¦ç´ ã¨ãªã‚‹å ´åˆ(ãƒãƒ¼ãƒ‰ãªã‚‚ã—ãã¯ï¼Œã‚¯ãƒªã‚¹ãƒ—ãªã‚¯ãƒ©ã‚¹ã‚¿ã¨ã„ã„ã¾ã™)ã‚„ï¼Œé€†ã«ä¸€ã¤ã®ã‚¯ãƒ©ã‚¹ã‚¿ãŒè¤‡æ•°ã®ã‚¯ãƒ©ã‚¹ã‚¿ã«åŒæ™‚ã«éƒ¨åˆ†çš„ã«æ‰€å±žã™ã‚‹å ´åˆ(ã‚½ãƒ•ãƒˆï¼Œã¾ãŸã¯ï¼Œãƒ•ã‚¡ã‚¸ã‚£ãªã‚¯ãƒ©ã‚¹ã‚¿ã¨ã„ã„ã¾ã™)ãŒã‚ã‚Šã¾ã™ï¼Žã“ã“ã§ã¯å‰è€…ã®ãƒãƒ¼ãƒ‰ãªå ´åˆã®ã‚¯ãƒ©ã‚¹ã‚¿ãƒªãƒ³ã‚°ã«ã¤ã„ã¦è¿°ã¹ã¾ã™ï¼Ž
sotarok 2009/07/29
ã‚¯ãƒ©ã‚¹ã‚¿ãƒ¼åˆ†æž / clustering

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Introduction to Information Retrieval
This is the companion website for the following book. Christopher D. Manning, Prabhakar Raghavan and Hinrich SchÃ¼tze, Introduction to Information Retrieval, Cambridge University Press. 2008. You can order this book at CUP, at your local bookstore or on the internet. The best search term to use is the ISBN: 0521865719. The book aims to provide a modern approach to information retrieval from a co
sotarok 2009/07/29
information retrieval

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http://www.sci.kagoshima-u.ac.jp/~ebsa/ishikawa01/contents.html
sotarok 2009/07/16
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sampling
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sotarok 2009/03/23
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sotarok 2009/01/15
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Data-Driven Enhancement of Facial Attractiveness
Data-Driven Enhancement of Facial AttractivenessTommer Leyvand, Daniel Cohen-Or, Gideon Dror and Dani LischinskiACM SIGGRAPH 2008 (To Appear) Abstract: When human raters are presented with a collection of shapes and asked to rank them according to their aesthetic appeal, the results often indicate that there is a statistical consensus among the raters. Yet it might be difficult to define a succinc
sotarok 2008/09/02
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sotarok 2008/03/13
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