A Power Customer Data Relational Algorithm Based on Magnanimity Fuzzy Address Matching

Abstract

According to the short text and unstructured characteristics of customer address, a data association fusion method for address has been proposed. In this method, the address was mapped to a digital fingerprint by improved Simhash technology, which effectively reduced the dimension of massive addresses and simplified the similarity-matching process of multi-source heterogeneous addresses. Furthermore, the weight setting of the eigenvector of the simhash algorithm was improved by introducing special weight gain. A two-level index mechanism was established by the characteristics of address division and data structure of digital fingerprints; the time-consuming digital fingerprint comparison was greatly reduced. The experimental results showed that calculation efficiency was greatly optimized; accuracy and coverage of the comparison were ensured. Through address matching of different databases, information fusion can be completed and the goal which power customers' demands is connected to power grid equipment is achieved.