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METHODS AND SYSTEMS OF OPERATING COMPUTERIZED NEURAL NETWORKS FOR MODELLING CSR-CUSTOMER RELATIONSHIPS

机译:用于建模CSR与客户关系的计算机化神经网络的方法和系统

摘要

In one aspect, a computerized method for operating computerized neural networks for modelling CSR-customer relationships includes the step of receiving a user query. The user query comprises a set of digital text from a customer as input into an online CSR system. The method includes the step of filtering out unnecessary content of the user query. The method includes the step of splitting filtered user query in a sentence wise manner. The method includes the step of feeding the tokenized user query into a contextualized word representation model. The method includes the step of generating a set of context-aware feature vectors from the contextualized word representation model. With the set of context-aware feature vectors, the method implements a decision-making function to generate an identified customer query. The method includes the step of receiving an agent response, wherein the agent response is a response to the user query, and wherein the agent response comprises a set of digital text from an agent. With an LSTM network, the method generates a user query tensor vector. With the LSTM network, generating an agent query tensor vector. The method includes the step of concatenating the user query tensor vector and the agent query tensor vector to produce a single tensor, wherein the single tensor is processable by a neural network.
机译:在一个方面,一种用于操作用于建模CSR-客户关系的计算机化神经网络的计算机化方法包括接收用户查询的步骤。用户查询包括来自客户的一组数字文本,作为在线CSR系统的输入。该方法包括过滤掉用户查询的不必要内容的步骤。该方法包括以句子明智的方式分割过滤的用户查询的步骤。该方法包括将令牌化用户查询输入到上下文化词表示模型中的步骤。该方法包括从上下文化的词表示模型生成一组上下文感知的特征向量的步骤。利用一组上下文感知特征向量,该方法实现了决策功能以生成识别的客户查询。该方法包括接收代理响应的步骤,其中代理响应是对用户查询的响应,并且其中代理响应包括来自代理的一组数字文本。在LSTM网络中,该方法生成用户查询张量向量。使用LSTM网络,生成代理查询张量向量。该方法包括将用户查询张量向量和代理查询张量向量连接起来以产生单个张量的步骤,其中该单个张量可以由神经网络处理。

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