Efficiently Browsing Text or Code in Emacs
Searching a large code base or text dumps for sections of interest can be frustrating. This article walks you through using Emacs to make the task easy. Sometimes grep just isn’t enough. Scenarios Let’s search the source code of Python 2.7.2 for something interesting. You may find yourself in similar circumstances for reasons like: You inherited an enormous project and you have to fix an elusive b
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1 åå‰ï¼šä»¥ä¸‹ã€åç„¡ã—ã«ã‹ã‚ã‚Šã¾ã—ã¦VIPãŒãŠé€ã‚Šã—ã¾ã™ ：2008/06/27(金) 22:46:49.84 ID:+l5iiHV90(´･ω･`)　ã“ã‚“ã«ã¡ã¯ã€‚今日ã¯æ¥½ã—ã„会話ã®ã‚³ãƒ„ã«ã¤ã„ã¦è€ƒãˆã¦ã¿ã¾ã—ょã†ã€‚ 4 åå‰ï¼šä»¥ä¸‹ã€åç„¡ã—ã«ã‹ã‚ã‚Šã¾ã—ã¦VIPãŒãŠé€ã‚Šã—ã¾ã™ ：2008/06/27(金) 22:47:33.18 ID:+l5iiHV90「人見知りã§äººã¨ä¼šè©±ãŒç¶šã‹ãªãã¦è¾›ã„ã€ã€Œã©ã†ä¼šè©±ã—ã¦ã„ã„ã‹ã‚ã‹ã‚‰ãªã„〠「身内ã¨ãªã‚‰ã„ãらã§ã‚‚話ã›ã‚‹ãŒã€è¦ªã—ããªã„人ã¨ã®ä¼šè©±ãŒè‹¦ç—›ã€ 「俺ãŒè©±ã—出ã™ã¨å ´ãŒå¼•ã„ã¦ã„ãã®ãŒã‚ã‹ã‚‹ãŠâ€¦â€¦ã©ã†ã„ã†ã“ã¨ã ãŠâ€¦â€¦ã€ ã¨ã„ã†ã‚ãªãŸã€ã€ä¸‰ã¤ã®åˆè¨€è‘‰ã€‘ã§ã€äººã¨ã®ä¼šè©±ã®è‹¦ç—›ã‚’ã‚’ã¡ã‚‡ã³ã£ã¨ã ã‘ ç·©å’Œã—ã¦ã¿ã¾ã›ã‚“ã‹ï¼Ÿ 6 åå‰ï¼šä»¥ä¸‹ã€åç„¡ã—ã«ã‹ã‚ã‚Šã¾ã—ã¦VIPãŒãŠé€ã‚Šã—ã¾ã™ ：2008/06/27(金) 22:48:03.21 ID:+l5iiHV90ã§ã¯ã€ã‚„る夫ã®ä½“験
Introduction to Information Retrieval #12 ã®å¾©ç¿’資料 - naoyaã®ã¯ã¦ãªãƒ€ã‚¤ã‚¢ãƒªãƒ¼
Introduction to Information Retrieval 輪èªä¼š 12ç« ã®å¾©ç¿’資料を以下ã«ã‚¢ãƒƒãƒ—ãƒãƒ¼ãƒ‰ã—ã¾ã—ãŸã€‚ http://bloghackers.net/~naoya/iir/ppt/iir_12.ppt 12ç« ã¯ã€ã¯ "Language models for information retrieval" ã¨ã„ã†ã“ã¨ã§ã€ç¢ºçŽ‡çš„è¨€èªžãƒ¢ãƒ‡ãƒ«ã‚’æƒ…å ±æ¤œç´¢ã«é©ç”¨ã™ã‚‹è©±ã§ã—ãŸã€‚ 確率的言語モデル 確率的言語モデルã¨ã¯ã€è‡ªç„¶è¨€èªžã‚’æ•°å¦çš„ã«æ‰±ã†ãƒ¢ãƒ‡ãƒ«ã«å˜èªžåˆ—ã€æ–‡å—列ãŒèµ·ã“る確率を与ãˆãŸã‚‚ã®ã§ã™ã€‚例ãˆã° "frog said that toad likes dog" ã¨ã„ã†å˜èªžåˆ— s ãŒã‚ã£ãŸã¨ã—ã¦ã€ãã‚Œãžã‚Œã®å˜èªžã®ç”Ÿèµ·ç¢ºçŽ‡ãŒä¸Žãˆã‚‰ã‚Œã¦ã„ã‚‹ã¨ã—ã¾ã™ã€‚ frog said that toad likes that dog M1 0.01 0.03 0.04 0.01 0.02 0.04
Burrows Wheeler Transform 㨠Suffix Array - naoyaã®ã¯ã¦ãªãƒ€ã‚¤ã‚¢ãƒªãƒ¼
,. -â€'''''""¨¨¨ヽ (.＿＿_,,,... -ｧァﾌ|　　　　　　　　　　ã‚…ã‚ã‚Šã®ã¾ã¾ 今日　起ã“ã£ãŸäº‹ã‚’話ã™ãœï¼ |i i|　 　 }!　}} /ï¼| |l､{　 　j}　/,,ｨ//｜　　　　　　　『BWT ã«ã¤ã„ã¦èª¿ã¹ã¦ã„ãŸã‚‰ Suffix Array ã®ãƒ©ã‚¤ãƒ–ラリãŒã§ãã¦ã„ãŸã€ i|:!ヾ､_ï¾‰ï¼ u {:}//ï¾ |ﾘ u' }　 ,ﾉ　_,!V,ﾊ | ï¼Â´fト､_{ï¾™{,ã‚£'ｅﾗ　, ﾀ人　　　　　　　　ãªâ€¦ã€€ä½•ã‚’言ã£ã¦ã‚‹ã®ã‹ã€€ã‚ã‹ã‚‰ãーã¨æ€ã†ãŒ /' 　 ヾ|宀| {´,)⌒`/ |<ヽﾄiã‚　　　　　　　　ãŠã‚Œã‚‚何をã•ã‚ŒãŸã®ã‹ã‚ã‹ã‚‰ãªã‹ã£ãŸâ€¦ ,ﾞ　 ï¼ )ヽ iLﾚ 　u' |　| ヾｌﾄﾊ〉 |ï¼_ï¼ã€€ ﾊ !ニ⊇　'ï¼:} 　V:::::ヽ　　　　　　　　é ãŒã©ã†ã«ã‹ãªã‚Šãã†ã ã£ãŸâ€¦ /ï¼ äºŒäºŒäºŒ7'T'' ï¼u'　__ /:::::::/｀ヽ /'
BWT 㨠PPM - naoyaã®ã¯ã¦ãªãƒ€ã‚¤ã‚¢ãƒªãƒ¼
Burrows Wheeler Transform (BWT, Block-sorting) 㨠Prediction by partial matching (PPM) ã¯æœ¬è³ªçš„ã«åŒã˜äº‹ã‚’ã‚„ã£ã¦ã„ã‚‹ã€ã¨ã„ã†ãŠè©±ã§ã™ã€‚ 先日 Managing Gigabytes ã‚’èªã‚“ã§ã„ãŸã¨ã“ã‚ã€P.69 㧠"block sorting is very closely related to the PPM* method, which is a variant of PPM that allows arbitrary-length contexts." ã¨ã„ã†è¨˜è¿°ãŒã‚ã‚Šã€ã©ã†ã«ã‚‚æ°—ã«ãªã£ãŸã®ã§èª¿ã¹ã¦ã¿ã¾ã—ãŸã€‚ サマリã¨ã—ã¦ã¯ã€BWT 㨠PPM ã®ä¸€ç¨®ã§ã‚ã‚‹ PPM* ã¯ã„ãšã‚Œã‚‚文脈ã‹ã‚‰æ¬¡ã®1æ–‡å—を一æ„ã«æ±ºå®šã™ã‚‹ã¨ã„ã†æ¦‚念ã§è¦‹ã‚‹ã¨æœ¬è³ªçš„ã«åŒã˜ã“ã¨ã‚’ã‚„ã£ã¦ã„ã‚‹ã¨è¨€ãˆã‚‹ã€ã¨ã„ã†ã¨ã“ã‚ã§ã™ã€‚ BWT ã®ã‚ら
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