Customer service repeated call treatment method based on cosine similarity text mining algorithm

Abstract

The invention discloses a customer service repeated call treatment method based on a cosine similarity text mining algorithm. The customer service repeated call treatment method comprises the following steps of extracting a work order text of 95598, performing data cleaning and removing abnormal call IDs; performing pretreatment on the data, extracting work orders of the same call and constructing a repeated call work order text set; converting the text into the language which can be recognized by a computer, establishing a vector space model, and representing the text by utilizing a characteristic vector; using a vector taking weight of a characteristic item as a component to express the whole text, measuring the similarity among documents on the basis of included angle cosine of two vectors in a use space of the characteristic vector, extracting a repeated call work order of the similar content of the same user by utilizing hierarchical clustering, and performing an analysis on semantic features; timely recording the problem reflected by the repeated call work order, sending an order and tracking a record. The customer service repeated call treatment method disclosed by the invention replaces manual search of the repeated call work order, and can improve the operating rate.

Description

Technical field [0001] The invention relates to a method for processing repeated calls to customer service based on a cosine similarity text mining algorithm. Background technique [0002] In recent years, with the rapid development of power business, the number of customers and business types have increased accordingly. The content of customer calls is complex and diverse. How to find useful information from the huge traffic volume is a huge challenge for customer service. According to the analysis of repeated calls, the semantic features hidden in the call information are excavated, focusing on customers with a large number of repeated calls, and timely discovering and tracking the hot issues of the calls, so as to grasp the best time to deal with the problems, thereby improving Ability to deal with hot issues and monitoring capabilities. Therefore, how to collect and discover customers' repeated call problems in the call information, semantic analysis of repeated calls, and a...

AI Technical Summary

Problems solved by technology

[0003] At present, there are many problems in the analysis of repeated work orders: the content of work order acceptance is text information, which is difficult to analyze, and the amount of information is large and unstructured, requiring manual review one by one, which is cumbersome and inefficient

There is little analysis of repeated calls, and it is impossible to understand the reasons for repeated calls from customers in time, resulting in customer service lag problems, so that it is impossible to respond to hot issues in a timely manner

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