Home Database Mysql Tutorial How can I implement fuzzy company name matching in MySQL with PHP for auto-completion?

How can I implement fuzzy company name matching in MySQL with PHP for auto-completion?

Dec 14, 2024 pm 04:52 PM

How can I implement fuzzy company name matching in MySQL with PHP for auto-completion?

Fuzzy Company Name Matching in MySQL with PHP for Auto-Completion

Introduction

Finding fuzzy matches for company names is a common task in autocomplete systems. This task can be challenging due to the large number of potentially matching companies and the need for efficient search algorithms.

Soundex Indexing

One approach to fuzzy matching is using Soundex indexing. Soundex is a phonetic algorithm that encodes words based on their pronunciation. This allows for approximate matching of words, even if they have different spellings. However, Soundex indexing has limitations, such as being unable to differentiate between longer strings and requiring the first letter to be the same.

Levenshtein Distance

A more advanced approach to fuzzy matching is using the Levenshtein distance. The Levenshtein distance measures the number of insertions, deletions, or substitutions required to transform one string into another. Unlike Soundex, this method does not have the disadvantages mentioned earlier.

Using Levenshtein Distance in PHP

The codejanitor.com website provides an example of a MySQL stored function that calculates the Levenshtein distance. You can use this function to perform fuzzy matching on company names as follows:

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// Load MySQL stored function (if not already loaded)

if (!function_exists('Levenshtein')) {

    $sql = "CREATE FUNCTION Levenshtein(s1 VARCHAR(255), s2 VARCHAR(255)) RETURNS INT

    BEGIN

        DECLARE lv_s1, lv_s2 VARCHAR(255);

        DECLARE lv_len1, lv_len2, lv_i, lv_j, lv_c, lv_cost INT;

        DECLARE lv_arr1[255] INT;

     

        SET lv_s1 = LOWER(s1);

        SET lv_s2 = LOWER(s2);

        SET lv_len1 = LENGTH(lv_s1);

        SET lv_len2 = LENGTH(lv_s2);

     

        -- Initialize the array

        SET lv_arr1[1] = 0;

        FOR lv_i = 1 TO lv_len1 DO

            SET lv_arr1[lv_i + 1] = lv_i;

        END FOR;

     

        -- Step 2

        FOR lv_j = 1 TO lv_len2 DO

            SET lv_c = lv_j;

            FOR lv_i = 1 TO lv_len1 DO

                IF SUBSTRING(lv_s1, lv_i, 1) = SUBSTRING(lv_s2, lv_j, 1) THEN

                    SET lv_cost = 0;

                ELSE

                    SET lv_cost = 1;

                END IF;

                SET lv_c = LEAST(lv_c + 1, lv_arr1[lv_i] + lv_cost, lv_arr1[lv_i - 1] + 1);

                SET lv_arr1[lv_i] = lv_c;

            END FOR;

        END FOR;

     

        RETURN lv_c;

    END;";

    $result = $mysqli->query($sql);

}

 

// Execute fuzzy matching query

$numWords = 0;

$userInput = "Microsift";

$query = "SELECT company_name, Levenshtein('$userInput', company_name) AS distance

          FROM companies

          ORDER BY distance ASC";

$result = $mysqli->query($query);

 

// Display results

while ($row = $result->fetch_assoc()) {

    $numWords++;

    echo $row['company_name'] . " (" . $row['distance'] . ")\n";

}

 

if ($numWords == 0) {

    echo "No matches found.\n";

}

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