Mathematical logic improves data quality, but not to the highest level. In order to meet all the needs of ensuring high data quality, knowledge of language and culture is required as well. After all, if you do not know what something means, how can you tell whether it is correct? It is in the application of human-like reasoning that Human Inference excels and makes the difference thanks to intensive research and development.
Why mathematical methods fail
Investments have led to the development of, among others, an intelligent interpretation of data. Why do we know that EVO AG and Gesellsch.f. Energieversorgung Offenbach are probably different notations for the same company? Humans can make this distinction in a split-second, but mathematical logic cannot. Even harder to distinguish for mathematical software is the difference between Leonard as a given name in Leonard Bates and Leonard as a surname in Leonard & Bates.
Knowledge-based interpretation
Intelligent interpretation uses knowledge dictionaries containing all possible elements that can appear in names and addresses, fit to your country. In addition, the dictionaries include properties for each element. They contain all possible meanings of various element-specific attributes, such as abbreviations, acronyms and adjectives. Rules for capitalization, punctuation and abbreviation are included for all elements. Finally, language-specific grammar rules are composed to recognize the structure of names and the context in which they appear.
The fact that the HIquality Product Suite is a knowledge-based solution ensures the highest level of data quality with low cost of ownership.
The whitepaper "Power of Knowledge" is available for more information on this subject. Please click here to go to the download section.
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