3.7 Entity Name
This is a bespoke rules-based algorithm that has been optimized for determining organization name matches. For example, BLUE SKYE COLLECTIONS LTD.
The process and methods to generate feature vector are similar to Individual Name. For more details, see Individual Name.
The process to derive the final score from the feature vector is different from Individual Name. The stopwords are not considered for computing the score. The stopwords for Entity Name are different from Individual Name.
Example:
- String 1: "BLUE SKYE COLLECTIONS LTD"
- String 2: "BLUE SKY THREE LTD"
- Stopword: LTD (It will not be considered for calculating the scrore)
The individual feature vector scores with overall scrore for the
match:
{"ced_list": [0, 1, 9, 0], "ced_min": 0, "ced_max": 9, "cmp": 54.545456, "wed_1": 1, "wed_2": 1, "wmc_1": 3, "wmc_2": 3, "wmp_1": 75.0, "wmp_2": 75.0, "metaphone": 3, "starts_with": 0, "abbreviation": 0, "tokenize_jaro": 0.8026768, "exact": 0, "inorderMaxPos": 0, "score": 0.95}