Yalian Zhang
ABSTRACT
Due to the unstructured and high-dimensional characteristics of repeated demand data from power customers, it is difficult to identify them. In order to improve the accuracy and efficiency of identifying duplicate demands from power customers, a fuzzy spectral clustering based model for identifying duplicate demands from power customers is proposed. Using the method of character vectorization, extract the features of power customer demand text, convert the power customer demand text into feature vector representation, and calculate the similarity of repeated demand word frequency for power customers based on these feature vectors. On this basis, fuzzy spectral clustering is used to construct a model for identifying repeated demands of power customers, achieving the recognition of repeated demands of power customers. The experimental results show that the proposed method can effectively improve the accuracy and efficiency of identifying repeated demands from power customers.
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Index Terms
- A Model for Identifying Repeated Demands from Power Customers Based on Fuzzy Spectral Clustering
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