levenshtein-distance

Here's a puzzle... I have two databases of the same 50000+ electronic products and I want to match products in one database to those in the other. However, the product names are not always identical. I've tried using the Levenshtein distance for measuring the string similarity however this hasn't worked. For example, -LG 42CS560 42-Inch 1080p 60Hz LCD HDTV -LG 42 Inch 1080p LCD HDTV These items are the same, yet their product names vary quite a lot. On the other hand... -LG 42 Inch 1080p LCD HDTV -LG 50 Inch 1080p LCD HDTV These are different products with very similar product names. How

I wish to create a fuzzy search algorithm. However, upon hours of research I am really struggling. I want to create an algorithm that performs a fuzzy search on a list of names of schools. This is what I have looked at so far: Most of my research keep pointing to " string metrics " on Google and Stackoverflow such as: Levenshtein distance Damerau-Levenshtein distance Needleman–Wunsch algorithm However this just gives a score of how similar 2 strings are. The only way I can think of implementing it as a search algorithm is to perform a linear search and executing the string metric algorithm for

UPDATE 3 Done. Below is the code that finally passed all of my tests. Again, this is modeled after Murilo Vasconcelo's modified version of Steve Hanov's algorithm. Thanks to all that helped! /** * Computes the minimum Levenshtein Distance between the given word (represented as an array of Characters) and the * words stored in theTrie. This algorithm is modeled after Steve Hanov's blog article "Fast and Easy Levenshtein * distance using a Trie" and Murilo Vasconcelo's revised version in C++. * * http://stevehanov.ca/blog/index.php?id=114 * http://murilo.wordpress.com/2011/02/01/fast-and-easy

Is it possible to include Levenshtein distance in a regular expression query? (Except by making union between permutations, like this to search for "hello" with Levenshtein distance 1: .ello | h.llo | he.lo | hel.o | hell. since this is stupid and unusable for larger Levenshtein distances.) is there possiblity how to include levenshtein distance in regular expression query? No, not in a sane way. Implementing - or using an existing - Levenshtein distance algorithm is the way to go. You can generate the regex programmatically. I will leave that as an exercise for the reader, but for the output

I recently implemented the UDFs of the Damerau–Levenshtein algorithms into MySQL, and was wondering if there is a way to combine the fuzzy matching of the Damerau–Levenshtein algorithm with the wildcard searching of the Like function? If I have the following data in a table: ID | Text --------------------------------------------- 1 | let's find this document 2 | let's find this docment 3 | When the book is closed 4 | The dcument is locked I want to run a query that would incorporate the Damerau–Levenshtein algorithm... select text from table where damlev('Document',tablename.text) <= 5; ..

According to an answer to another question , in sqlite the Levenshtein distance is implemented in a SQL function called editdist3 . (Compare also the documentation ) Now when I try to use it, all I get is an error that it doesn’t exist: ╰┄┄> sqlite3 SQLite version 3.11.1 2016-03-03 16:17:53 Enter ".help" for usage hints. Connected to a transient in-memory database. Use ".open FILENAME" to reopen on a persistent database. sqlite> CREATE TABLE test (col1 TEXT); sqlite> INSERT INTO test VALUES ('foobar'); sqlite> SELECT * FROM test WHERE editdist3(col1, 'f00bar') < 3; Error: no such function:

I'm searching for an implementations of the Damerau–Levenshtein algorithm for PHP, but it seems that I can't find anything with my friend google. So far I have to use PHP implemented Levenshtein (without Damerau transposition, which is very important), or get a original source code (in C, C++, C#, Perl) and write (translate) it to PHP. Does anybody have any knowledge of a PHP implementation ? I'm using soundex and double metaphone for a "Did you mean:" extension on my corporate intranet, and I want to implement the Damerau–Levenshtein algorithm to help me sort the results better. Something

Does Apaches Solr search engine provide approximate string matches, e.g. via Levenshtein algorithm? I'm looking for a way to find customers by last name. But I cannot guarantee the correctness of the names. How can I configure Solr so that it would find the person "Levenshtein" even if I search for "Levenstein" ? Typically this is done with the SpellCheckComponent , which internally uses the Lucene SpellChecker by default, which implements Levenshtein. The wiki really explains very well how it works, how to configure it and what options are available, no point repeating it here. Or you could