Quasi-Succinct Indices
Compressed inverted indices in use today are based on the idea of gap compression: documents pointers are stored in increasing order, and the gaps between successive document pointers are stored using suitable codes which represent smaller gaps using less bits. Additional data such as counts and positions is stored using similar techniques. A large body of research has been built in the last 30 ye
MG4J: high-performance text indexing for Javaâ„¢
Introduction MG4J is a free full-text search engine for large document collections written in Java. MG4J is a highly customisable, high-performance, full-fledged search engine providing state-of-the-art features (such as BM25/BM25F scoring) and new research algorithms. The main points of MG4J are: Powerful indexing. Support for document collections and factories makes it possible to analyse, index
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Solr vs Elasticsearch: Performance Differences & More - Sematext
“Solr or Elasticsearch?â€â€¦well, at least that is the common question we hear from Sematext’s consulting services clients and prospects. Which one is better, Solr or Elasticsearch? Which one is faster? Which one scales better? Which one is easier to manage? Which one should we use? Is there any advantage to migrating from Solr to Elasticsearch? – and the list goes on. These are all great questions,
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Elastic — The Search AI Company
Search and analytics, data ingestion, and visualization – all at your fingertips.
Stupid Solr tricks: Introduction (SST #0) – Robot Librarian
Completed parts of the series: A Solr Field Type for numeric(ish) IDs Using localparams in Solr (or, how to boost records that contain all terms) Requiring/Preferring searches that don’t span multiple values Boosting on Exactish (anchored) phrase matching Those of you who read this blog regularly (Hi Mom!) know that while we do a lot of stuff at the University of Michigan Library, our bread-and-bu
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Wordpress 試験é‹ç”¨ã¯çµ‚了ã—ã¾ã—ãŸã€‚
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‚‚広ãæ™®åŠã—ã¦ã„ã‚‹ç”»åƒç‰¹å¾´è¡¨ç¾ã§ã€ç”»åƒä¸ã®å¤šæ•°ã®å±€æ‰€ç‰¹å¾´ã‚’ベクトルé‡å化ã—ヒストグラムã«ã—ãŸã‚‚ã®ã§ã™ã€‚最近ã¯OpenCVãªã©ã®ãƒ„ール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„部分ã§ã¤ã¾ã¥ãã“ã¨ã‚‚多ã„ã®ã§ã¯ãªã„ã§ã—ょã†ã‹ã€‚最新ã®ç ”究ã§ã¯èªè˜ç²¾åº¦ãŒé£›èºçš„ã«å‘上ã—ã¦ã„ã¾ã™ãŒã€å±€æ‰€ç‰¹å¾´æŠ½å‡ºãªã©ã®ç´°ã‹ã„ノウãƒã‚¦ã®è“„ç©ã«ã‚ˆã‚‹éƒ¨åˆ†ã‚‚ã‹ãªã‚Šå¤§ãã„ã¨æ€ã„ã¾ã™ã€‚ （ãã®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‰ 以下ã€è‡ªåˆ†ãŒæŠŠæ¡ã—ã¦ã„るノウãƒã‚¦ã‚’ã¾ã¨ã‚ã¦ã¿ãŸã„ã¨æ€ã„ã¾ã™ã€‚ãŸã ã—ã€ç§è‡ªèº«ã®çµŒé¨“や主観ã«åŸºã¥ãã‚‚ã®ã§ã‚ã‚Šã€çµ¶å¯¾çš„ãªã‚‚ã®ã§ã¯ãªã„ã“ã¨ã«ã”注æ„ãã 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©
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Apache Solr を利用ã—ãŸæ¤œç´¢ãƒ‘ッケージ Anuenue - mixi engineer blog
ç ”ç©¶é–‹ç™ºã‚°ãƒ«ãƒ¼ãƒ—ã® takahi-i ã§ã™ã€‚ 先日åå‰ã ã‘ã”紹介ã—ãŸAnuenue ã¨ã„ã†ãƒ„ールをã”紹介ã•ã›ã¦ã„ãŸã ãã¾ã™ã€‚Anuenue 㯠Apache Solr ã®ãƒ©ãƒƒãƒ‘ーã§ã‚ã‚Šã€æ¤œç´¢ã‚¯ãƒ©ã‚¹ã‚¿ã®æ§‹ç¯‰ã¨é‹ç”¨ã‚’容易ã«ã™ã‚‹ç›®çš„ã§åˆ¶ä½œã•ã‚Œã¾ã—ãŸã€‚ 本稿ã§ã¯å§‹ã‚ã« Apache Solr ã‚’é¸æŠžã—ãŸç†ç”±ã«ã¤ã„ã¦è¿°ã¹ã€ãã®å¾Œã€ã“ã®ãƒ„ールを開発ã—ãŸèƒŒæ™¯ã¨ãã®ç›®çš„ã‚’ã”紹介ã•ã›ã¦ã„ãŸã ãã¾ã™ã€‚後åŠã§ã¯å®Ÿéš›ã« Anuenue を用ã„ã¦æ¤œç´¢ã‚¯ãƒ©ã‚¹ã‚¿ã‚’ç«‹ã¡ä¸Šã’ã¾ã™ã€‚ ãªãœ Apache Solr を採用ã—ãŸã®ã‹ 昨年ã®ç§‹ã€å¼Šç¤¾ã®æ¤œç´¢ã‚¨ãƒ³ã‚¸ãƒ³ã‚’ç½®ãæ›ãˆã‚‹ã¨ã„ã†è¨ˆç”»ãŒç¤¾å†…ã§ç–定ã•ã‚Œã€ãƒ™ãƒ¼ã‚¹ã¨ãªã‚‹æ¤œç´¢ã‚¨ãƒ³ã‚¸ãƒ³ã®é¸å®šã®ãŸã‚ã«å¤šãã® OSS 検索エンジンを比較検討ã—ã¾ã—ãŸã€‚ã“ã®ã¨ãé‡è¦–ã—ãŸã®ã¯ä¸€å°ã®æ¤œç´¢ãƒ‘フォーマンスã¨åŒæ™‚ã«ã€ä¿å®ˆã®å®¹æ˜“ã•ã¨ã€é–‹ç™ºã‚³ãƒŸãƒ¥ãƒ‹ãƒ†ã‚£ã®è¦æ¨¡ã§ã™ã€‚ 検索エンジンã®ä¿å®ˆæ€§ã«é–¢ã—ã¦ç‰¹ã«é‡è¦ã¨è€ƒãˆãŸã®
Chrome ウェブストア
Google Chrome ã®ã™ã°ã‚‰ã—ã„アプリã€ã‚²ãƒ¼ãƒ ã€æ‹¡å¼µæ©Ÿèƒ½ã€ãƒ†ãƒ¼ãƒžã‚’ãœã²ã”利用ãã ã•ã„。
SIGIR 2011 Previews
Accepted SIGIR 2011 authors have started posting their papers online, so I have decided to collect them here. Please comment on the ones you think are the most interesting and important. As I get more papers, I’ll edit this post to add them. http://bit.ly/kMWe1b Lidan Wang, Jimmy Lin, and Don Metzler, “A Cascade Ranking Model for Efficient Ranked Retrieval†http://bit.ly/iYr7HB Nima Asadi, Don M
Lucene Revolution 2011 ã«å‚åŠ ã—ã¾ã—㟠- mixi engineer blog
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Googleアルゴリズム200é …ç›®å…¨ã¦ã‚’特別公開 – 店舗集客マーケティングブãƒã‚°
Googleアルゴリズムã®200ã®è¦ç´ を発見ã—ã¾ã—ょã†ï¼ï¼ˆLet’s Try to Find All 200 Parameters in Google Algorithm） ã¯2009å¹´ã«æ›¸ã‹ã‚ŒãŸè¨˜äº‹ã§ã™ãŒã€ãƒ‘ンダアップデートãŒé©ç”¨ã•ã‚ŒãŸä»Šç¾åœ¨ï¼ˆ2011å¹´4月）ã§ã‚‚é‡è¦é …ç›®ãŒå¤šã書ã‹ã‚Œã¦ã„ã‚‹ã‚‚ã®ã§ã€‚ 多ãã¯Googleã®ç‰¹è¨±ï¼ˆåˆè¡†å›½ç‰¹è¨±å‡ºé¡˜0050071741）ã«åŸºã¥ã„ã¦ã„ã¾ã™ãŒã€ç†è€…ã®ã‚¢ãƒ³ãŒè‡ªèº«ã®è§£æžçµæžœã‚„予測を盛り込んã§ã„る事ã§ã€ã‚ˆã‚Šå®Ÿè·µã«è¿‘ã„内容ã«ãªã£ã¦ã„ã¾ã™ã€‚ SEOåˆå¿ƒè€…ã®æ–¹ã¯ã€ã“ã‚Œã‹ã‚‰ã®ã‚¦ã‚§ãƒ–制作ã®è»¸ã«ã€SEOエã‚スパートã®æ–¹ã¯ã‚‚ã†ä¸€åº¦è‡ªèº«ã®ã‚µã‚¤ãƒˆã‚’見直ã™ç›®æ¬¡ã¨ã—ã¦ç¢ºèªã—ã¦ã¿ã¦ã¯ã„ã‹ãŒã§ã—ょã†ã‹ã€‚ ドメインã«é–¢ã™ã‚‹13è¦å› ドメイン年齢 ドメインå–å¾—ã‹ã‚‰ã®é•·ã• ãƒ‰ãƒ¡ã‚¤ãƒ³ç™»éŒ²æƒ…å ±ï¼ˆWho isæƒ…å ±ï¼‰ã®è¡¨ç¤º/éžè¡¨ç¤º ドメイン種類（サイトレベルドメイン（.com ã‚„ co.uk） ト
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