Intelligent message pushing method based on NLP deep learning
A message push and deep learning technology, applied in the information field, can solve the problems of information leakage, poor effect, high cost of collection technology, etc., and achieve the effect of simple data interaction
Pending Publication Date: 2020-11-03
武汉众邦银行股份有限公司
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[0006] The purpose of the content of the present invention is to solve the problems of high cost, poor effect and serious information leakage of the existing collection technology. The present invention provides an intelligent collection method based on NLP deep learning
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[0069] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, and are not intended to limit the present invention, that is, the described embodiments are only some of the embodiments of the present invention, but not all of the embodiments. The components of the embodiments of the invention generally described and illustrated in the figures herein may be arranged and designed in a variety of different configurations.
[0070] Accordingly, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the invention. Based on the embodiments of the...
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The invention relates to the technical field of information, and provides an intelligent message pushing method based on NLP deep learning, and an intelligent collection method for customers accurately according to customer scores. The objective of the invention is to solve the problems of high cost, poor collection effect, malicious leakage of customer information and customer complaints caused by improper collection in the current collection industry. According to the main scheme, the method comprises the steps that 1, data collection is conducted, specifically, collected objects are collected, useful information is inserted into an information base, and data is processed according to information of the information base to become quantitative indexes; 2, intelligent case division: different strategies are grouped on the collection objects according to the quantitative indexes. 3, intelligent collection: according to a grouping strategy, clients are collected, voice is recognized through an ASR technology, natural language is processed through an NLP technology, and voice is synethsized through a TTS technology, so that the collection mode is more efficient, the collection resultis more structured, and machine learning is facilitated. 4, intelligent labeling: according to a user result, classified statistics is performed on a collection result, so that the next collection ismore accurate and efficient.
Description
technical field [0001] The invention relates to the field of information technology, and provides a method for intelligently pushing collection information to customers based on NLP deep learning technology and accurately according to customer ratings. Background technique [0002] With the rapid development of my country's economy, residents' consumption awareness and consumption ability of card holders have been significantly enhanced, and my country's consumer credit has entered a stage of large-scale development. After the initial realization of the development goals, domestic consumer credit has become more and more formalized and scaled. In the future, consumer credit will occupy an important place in the market, not only helping individuals with financial needs, but also helping small, medium and micro enterprises meet their financial needs. In order to win in the fierce market competition, while the consumer credit of our bank is growing rapidly, we aim to maximize ...
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IPC IPC(8): G06Q40/02G06Q20/40G06F16/215G06F16/2458G06F16/248G06F40/30H04M3/51
CPCG06Q20/4016G06F16/215G06F16/2462G06F16/2465G06F16/248G06F40/30H04M3/5166G06F2216/03G06Q40/03
Inventor 李烨李耀彭磊薛伟
Owner 武汉众邦银行股份有限公司