What are the best practices for creating a robust algorithm to match hotel names with cities in a PHP-based data analysis tool?

To create a robust algorithm to match hotel names with cities in a PHP-based data analysis tool, it is important to use a combination of string matching techniques, such as Levenshtein distance or regular expressions, along with a comprehensive database of hotel names and city names. Additionally, implementing error handling mechanisms and considering variations in naming conventions will improve the accuracy of the matching algorithm. 

function matchHotelWithCity($hotelName, $cityList) {
    $bestMatch = '';
    $minDistance = PHP_INT_MAX;

    foreach ($cityList as $city) {
        similar_text($hotelName, $city, $percent);
        
        if ($percent > 80 && $percent < $minDistance) {
            $bestMatch = $city;
            $minDistance = $percent;
        }
    }

    return $bestMatch;
}

// Example of how to use the matchHotelWithCity function
$hotelName = "Hotel ABC";
$cityList = ["New York City", "Los Angeles", "Chicago", "San Francisco"];

$matchedCity = matchHotelWithCity($hotelName, $cityList);
echo "The hotel '$hotelName' is located in $matchedCity.";

Keywords

string manipulation regular expressions data cleansing fuzzy matching Levenshtein distance

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