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Fuzzy Mathching (Mplus)
Structuring and standardization of unstructured data such as addresses and company names etc., and techniques for fuzzy matching comparison.

Unstructured data has long occupied a large capacity of historical data, however, which has not been well served for analysis, and even is difficult to be managed, including data validation and data standardization. This has caused the great deal of storage of a large number of unstructured data such as addresses and company names for a long time without playing their own value .

SCAI fuzzy matching technology includes standardization and fuzzy comparison processing of unstructured data, which can both standardized process addresses and company names to facilitate data management and data application, and make fuzzy comparison of data such as addresses and company names to explore the similarities and differences of these unstructured data, and provide analysis factors for automatic information comparison, list fuzzy comparison, marketing and fraud detection. SCAI applies Chinese fuzzy matching technology based on local massive data R&D and validation such as statistics-based multi-meaning probability vocabulary, customized grammar, homophone matching, word-cutting strategy table, regular expression etc., which can provides high-precision fuzzy matching of addresses and company names at the beginning, also provides users with the freedom to expand and customize in the future, and fully meet the needs of business development.

Fraud Detection and Prevention