基于深度学习与自然语言处理技术的智能客服机器人在制造业中的应用研究

Research on the Application of Intelligent Customer Service Robot Based on Deep Learning and Natural Language Processing Technology in Manufacturing Industry

利用机器人中的自然语言处理技术,进行终端用户信息的主动检索、文字数据信息的标注,通过对标签文字的分析,实现对制造企业中敏感顾客画像的多特征感知,并利用深度学习算法中的卷积神经网络,进行制造业营销文本数据的训练,将训练结果进行压缩和融合,输入到分类器中分类。在此基础上,进行服务项目与用户需求信息之间匹配度的计算,如匹配度较高,即可以为该用户提供此项服务,反之则不需要为该用户提供此类服务。实例应用实验结果表明:设计方法的应用效果良好,为制造企业在市场内的发展创造了更高的经济效益。

Using the natural language processing technology in the robot, the active retrieval of terminal user information and the annotation of text data information are carried out. Through the analysis of label text, the multi-feature perception of sensitive customer portraits in manufacturing enterprises is realized. Using the convolutional neural network in the deep learning algorithm to train the manufacturing marketing text data, the training results are compressed and fused, and input into the classifier for classification;On this basis, the matching degree between the service project and the user 's demand information is calculated. If the matching degree is high, the service can be provided for the user, otherwise it is not necessary to provide such services for the user. The experimental results show that the application effect of the design method is good. and create higher economic benefits for the development of manufacturing enterprises in the market.