Comments on: Doing Relevance Ranked Full-Text Searches In MySQL http://maisonbisson.com/blog/post/10752/making-mysql-do-relevance-ranked-full-text-searches/ A bunch of stuff I would have emailed you about. Wed, 04 Nov 2009 23:52:48 -0800 http://wordpress.org/?v=2.8.4 hourly 1 By: Rohan Shenoy http://maisonbisson.com/blog/post/10752/making-mysql-do-relevance-ranked-full-text-searches/comment-page-1/#comment-191827 Rohan Shenoy Tue, 01 Apr 2008 16:11:47 +0000 http://maisonbisson.com/blog/?p=10752#comment-191827 Thanks Maison, was looking for it. I wanted to sort the results of SELECT query by releveance. But I was stuck with '%LIKE%'. You have helped me out. Thanks a lot dear! Thanks Maison, was looking for it. I wanted to sort the results of SELECT query by releveance. But I was stuck with ‘%LIKE%’. You have helped me out.

Thanks a lot dear!

]]> By: taz4mfsd http://maisonbisson.com/blog/post/10752/making-mysql-do-relevance-ranked-full-text-searches/comment-page-1/#comment-191126 taz4mfsd Sat, 08 Mar 2008 23:21:36 +0000 http://maisonbisson.com/blog/?p=10752#comment-191126 sexy gierls sexy gierls

]]> By: Epsilon-Delta » Dissecting MySQL Fulltext Indexing http://maisonbisson.com/blog/post/10752/making-mysql-do-relevance-ranked-full-text-searches/comment-page-1/#comment-37670 Epsilon-Delta » Dissecting MySQL Fulltext Indexing Wed, 17 May 2006 17:25:36 +0000 http://maisonbisson.com/blog/?p=10752#comment-37670 [...] MySQL provides two types of fulltext searches - boolean and natural language. I’m going to focus on the natural language search because it is more mathematically intense. The underlying concept behind the method used in MySQL is that each term in each document is assigned a specific weight which is used to decide a query’s “distance” or “score” with respect to that document. The weights are assigned such that the weight is increased if the term occurs frequently in the document, but decreased in the term occurs frequently among all documents. For a description of how the weights are computed, check out the MySQL documentation. For the curious reader, this article also explains the computation of word-document weights. There are also a slew of articles on using fulltext search in practice. [...] [...] MySQL provides two types of fulltext searches – boolean and natural language. I’m going to focus on the natural language search because it is more mathematically intense. The underlying concept behind the method used in MySQL is that each term in each document is assigned a specific weight which is used to decide a query’s “distance” or “score” with respect to that document. The weights are assigned such that the weight is increased if the term occurs frequently in the document, but decreased in the term occurs frequently among all documents. For a description of how the weights are computed, check out the MySQL documentation. For the curious reader, this article also explains the computation of word-document weights. There are also a slew of articles on using fulltext search in practice. [...]

]]> By: mansoor http://maisonbisson.com/blog/post/10752/making-mysql-do-relevance-ranked-full-text-searches/comment-page-1/#comment-36273 mansoor Fri, 28 Apr 2006 21:27:21 +0000 http://maisonbisson.com/blog/?p=10752#comment-36273 salam dostaneh man harkasi keh mikad ba yek pesarehg 29 saleh mogarad va lisanseh mekanik az thran azdevag koneh ageh be tafahoom residim baram emall bezareh salam dostaneh man harkasi keh mikad ba yek pesarehg 29 saleh mogarad va lisanseh mekanik az thran azdevag koneh ageh be tafahoom residim baram emall bezareh

]]> By: Is Sun’s T2000 Up To It? « MaisonBisson.com http://maisonbisson.com/blog/post/10752/making-mysql-do-relevance-ranked-full-text-searches/comment-page-1/#comment-32253 Is Sun’s T2000 Up To It? « MaisonBisson.com Mon, 27 Feb 2006 01:33:39 +0000 http://maisonbisson.com/blog/?p=10752#comment-32253 [...] And I’m fully confident that when I put our entire catalog into WPopac, all 330,000 bib records (resulting in about 6.2 million atomic records), performance will still be up to the task. And my math suggests everything should be ducky on a relatively budget server up beyond about 1 million bib records), but what happens for libraries that have more than that, say, perhaps 6 to 8 million bib records (again, 110 to 150 million atomic records; again, all full-text indexed in MySQL)? [...] [...] And I’m fully confident that when I put our entire catalog into WPopac, all 330,000 bib records (resulting in about 6.2 million atomic records), performance will still be up to the task. And my math suggests everything should be ducky on a relatively budget server up beyond about 1 million bib records), but what happens for libraries that have more than that, say, perhaps 6 to 8 million bib records (again, 110 to 150 million atomic records; again, all full-text indexed in MySQL)? [...]

]]> By: Pulni´s private News » Volltextsuche http://maisonbisson.com/blog/post/10752/making-mysql-do-relevance-ranked-full-text-searches/comment-page-1/#comment-31809 Pulni´s private News » Volltextsuche Tue, 14 Feb 2006 17:33:10 +0000 http://maisonbisson.com/blog/?p=10752#comment-31809 [...] MySQL provides two types of fulltext searches - boolean and natural language. I’m going to focus on the natural language search because it is more mathematically intense. The underlying concept behind the method used in MySQL is that each term in each document is assigned a specific weight which is used to decide a query’s “distance” or “score” with respect to that document. The weights are assigned such that the weight is increased if the term occurs frequently in the document, but decreased in the term occurs frequently among all documents. For a description of how the weights are computed, check out the MySQL documentation. For the curious reader, this article also explains the computation of word-document weights. There are also a slew of articles on using fulltext search in practice. [...] [...] MySQL provides two types of fulltext searches – boolean and natural language. I’m going to focus on the natural language search because it is more mathematically intense. The underlying concept behind the method used in MySQL is that each term in each document is assigned a specific weight which is used to decide a query’s “distance” or “score” with respect to that document. The weights are assigned such that the weight is increased if the term occurs frequently in the document, but decreased in the term occurs frequently among all documents. For a description of how the weights are computed, check out the MySQL documentation. For the curious reader, this article also explains the computation of word-document weights. There are also a slew of articles on using fulltext search in practice. [...]

]]> By: Epsilon-Delta: Mathematics and Computer Programming » Dissecting MySQL Fulltext Indexing http://maisonbisson.com/blog/post/10752/making-mysql-do-relevance-ranked-full-text-searches/comment-page-1/#comment-31646 Epsilon-Delta: Mathematics and Computer Programming » Dissecting MySQL Fulltext Indexing Thu, 09 Feb 2006 01:53:12 +0000 http://maisonbisson.com/blog/?p=10752#comment-31646 [...] MySQL provides two types of fulltext searches - boolean and natural language. I’m going to focus on the natural language search because it is more mathematically intense. The underlying concept behind the method used in MySQL is that each term in each document is assigned a specific weight which is used to decide a query’s “distance” or “score” with respect to that document. The weights are assigned such that the weight is increased if the term occurs frequently in the document, but decreased in the term occurs frequently among all documents. For a description of how the weights are computed, check out the MySQL documentation. For the curious reader, this article also explains the computation of word-document weights. There are also a slew of articles on using fulltext search in practice. [...] [...] MySQL provides two types of fulltext searches – boolean and natural language. I’m going to focus on the natural language search because it is more mathematically intense. The underlying concept behind the method used in MySQL is that each term in each document is assigned a specific weight which is used to decide a query’s “distance” or “score” with respect to that document. The weights are assigned such that the weight is increased if the term occurs frequently in the document, but decreased in the term occurs frequently among all documents. For a description of how the weights are computed, check out the MySQL documentation. For the curious reader, this article also explains the computation of word-document weights. There are also a slew of articles on using fulltext search in practice. [...]

]]> By: Plesk Bites « MaisonBisson.com http://maisonbisson.com/blog/post/10752/making-mysql-do-relevance-ranked-full-text-searches/comment-page-1/#comment-30429 Plesk Bites « MaisonBisson.com Fri, 27 Jan 2006 00:59:52 +0000 http://maisonbisson.com/blog/?p=10752#comment-30429 [...] Why? Because MySQL 3.x doesn’t support query caching, boolean full-text searching, or complex subqueries. [...] [...] Why? Because MySQL 3.x doesn’t support query caching, boolean full-text searching, or complex subqueries. [...]

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