Many times on a product page you will want to show the shopper some similar products they might also be interested in. I struggled with this for a long time before I discovered this solution, which I think works very well. The Levenstein distance is a measure of how different 2 comparing strings are.
I found a great implementation for a Levenstein Distance function in MySQL by Jason Rust. I had to make one small adjustment to get MySQL to allow me to create it, which was simply changing the delimiter from ; to something else since the function definition contains semicolons in it.
So the updated code would be:
DELIMITER $$ CREATE FUNCTION levenshtein( s1 VARCHAR(255), s2 VARCHAR(255) ) RETURNS INT DETERMINISTIC BEGIN DECLARE s1_len, s2_len, i, j, c, c_temp, cost INT; DECLARE s1_char CHAR; -- max strlen=255 DECLARE cv0, cv1 VARBINARY(256); SET s1_len = CHAR_LENGTH(s1), s2_len = CHAR_LENGTH(s2), cv1 = 0x00, j = 1, i = 1, c = 0; IF s1 = s2 THEN RETURN 0; ELSEIF s1_len = 0 THEN RETURN s2_len; ELSEIF s2_len = 0 THEN RETURN s1_len; ELSE WHILE j <= s2_len DO SET cv1 = CONCAT(cv1, UNHEX(HEX(j))), j = j + 1; END WHILE; WHILE i <= s1_len DO SET s1_char = SUBSTRING(s1, i, 1), c = i, cv0 = UNHEX(HEX(i)), j = 1; WHILE j <= s2_len DO SET c = c + 1; IF s1_char = SUBSTRING(s2, j, 1) THEN SET cost = 0; ELSE SET cost = 1; END IF; SET c_temp = CONV(HEX(SUBSTRING(cv1, j, 1)), 16, 10) + cost; IF c > c_temp THEN SET c = c_temp; END IF; SET c_temp = CONV(HEX(SUBSTRING(cv1, j+1, 1)), 16, 10) + 1; IF c > c_temp THEN SET c = c_temp; END IF; SET cv0 = CONCAT(cv0, UNHEX(HEX(c))), j = j + 1; END WHILE; SET cv1 = cv0, i = i + 1; END WHILE; END IF; RETURN c; END$$And the helper function:
DELIMITER $$ CREATE FUNCTION levenshtein_ratio( s1 VARCHAR(255), s2 VARCHAR(255) ) RETURNS INT DETERMINISTIC BEGIN DECLARE s1_len, s2_len, max_len INT; SET s1_len = LENGTH(s1), s2_len = LENGTH(s2); IF s1_len > s2_len THEN SET max_len = s1_len; ELSE SET max_len = s2_len; END IF; RETURN ROUND((1 - LEVENSHTEIN(s1, s2) / max_len) * 100); END$$
Once you have those defined you can use it to find related products by their vendor style number. Most manufacturers use a common scheme for their style numbers so the closest matching style numbers are usually the most similar products. With that in mind, you could now find simiilar products with a query like this:
SELECT *, levenshtein(style_number, "style-number-to-match") as related_score FROM products ORDER BY related_score LIMIT 2
This will give you the 2 most matching products (the first one being itself). Also note, this function is very time consuming so to speed it up I limited it to only products with the same brand. You also want to exclude the same product from returning in the result set.
SELECT *, levenshtein(style_number, "style-number-to-match") as related_score FROM products WHERE brand = "my-brand" AND style_number != "style-number-to-match" ORDER BY related_score LIMIT 2
Even still, if you have many products this seems too slow to use in production. So what I did was use ajax to find the related products after the page finished loading so it does not make the entire page slow. A small price to pay to get very accurate related products.