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Use SOUNDEX() word by word on SQL Server

开发者 https://www.devze.com 2022-12-14 19:16 出处:网络
Here is my problem. For example I have开发者_运维问答 a table Products that contains a field, Name:

Here is my problem. For example I have开发者_运维问答 a table Products that contains a field, Name:

Products
ID | Name | ..
1  | "USB Key 10Go"
2  | "Intel computer"
3  | "12 inches laptop computer"
...

I'm currently implementing a simple search engine (SQL Server and ASP .NET, C#) for an iPhone web-app and I would like to use the SOUNDEX() SQL Server function.

The thing is, I can't directly use SOUNDEX on the Name field. (This would be irrelevant since there are several words in the name.) I would like to apply the SOUNDEX function to each word from the Name field, and then see if any of them matches the researched keyword.

If someone has any clue how to do this, that would be awesome.


Rather than use Soundex you might be better off computing the Levenshtein distance between the two strings. See the Wikipedia article on Levenshtein distance.

There's a TSQL implementation of the Levenshtein distance algorithm here.

Share and enjoy.


EDIT 03-May-2012

Since writing my original response I've learned that Oracle includes the Levenshtein distance and several other "string similarity" functions in the UTL_MATCH package, which I believe is a standard part of the database. Documentation here. Perhaps not directly related to the original post (which was for SQL Server) but perhaps useful as many shops use multiple databases.


Have you looked into the Full-Text Search feature in SQL Server? I know this is not exactly what you asked for. Its just that the SOUNDEX() function is used to find similar SOUNDING names (EX: SMITH and SMYTHE sound the same). In a search engine, however, how a word sounds is less important than the search words themselves. Full-Text Search also lets you use synonyms (allowing you to specify certain words that mean the same thing within your application's context), and have them automatically considered during your search.

Look at these pages for more information about Full Text Search in SQL Server:

Introduction to Full-Text Search

CONTAINS

CONTAINSTABLE

FREETEXT

FREETEXTTABLE


If you have to do it all in the RDBMS, a UDF would be the best if it's an option.

Otherwise, you could use this technique to at least soundex the first four words individually using PARSENAME:

From How do I split a string so I can access item x?:

PARSENAME(REPLACE('12 inches laptop computer', ' ', '.'), 1)  --return computer
PARSENAME(REPLACE('12 inches laptop computer', ' ', '.'), 2)  --return laptop
...

However: using PARSENAME in this way is a hack and a serious limitation is it only works for a max of 4 parts. If there are 5 or more words PARSENAME will return NULL, so you have to check for that with a conditional and degrade gracefully.

Here's a simplified example (again, without the NULL checks)

SELECT *
FROM Products 
WHERE SOUNDEX(search_input) = SOUNDEX(PARSENAME(REPLACE(Name, ' ', '.'), 4))
  OR SOUNDEX(search_input) = SOUNDEX(PARSENAME(REPLACE(Name, ' ', '.'), 3))
  OR SOUNDEX(search_input) = SOUNDEX(PARSENAME(REPLACE(Name, ' ', '.'), 2))
  OR SOUNDEX(search_input) = SOUNDEX(PARSENAME(REPLACE(Name, ' ', '.'), 1))


The SOUNDEX may be a perfect fit for your purpuse, but please remember that it may not provide good results for anything else than british or american english spoken words! It may even be used on german phonetical spoken words, but it will not work well with ANYTHING else.


You could try storing the metaphone of each word concatenated with hyphens. EG stored_metaphone field could contain something like '-AKTRF-SPLS-'. Then build a query like this:

$where = '(';
$search_sql = array();
$search_terms = explode(' ',$search);
foreach ($search_terms as $term) {
    $search_sql[] = "`stored_metaphone` LIKE '%-".metaphone($term)."-%'";
}
$where .= implode(' OR ',$search_sql);
$where .= ')';

NB this is only the WHERE part of the query.

As far as I know metaphone only works with English. The above sql is working rather well on a number of sites.

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