Analysis And Design Of Intelligent Customer Service System Based On User Scenario

In recent years,the Internet has developed rapidly.The traditional offline transactions have been largely transferred to the Internet driven by the Internet.Due to the virtual nature of online transactions,it is difficult to ensure the quality of the products and the difficulty of user consultation.In addition,consumers are increasingly concerned about the quality of services.It is very important for the customer to participate in online transactions.However,at present,China's e-commerce market is huge,and the number of online shopping users is very large.The customer service is faced with a great deal of work pressure.In addition,customer service also has difficulties in recruiting,high labor costs,and a high turnover rate.It is beneficial for the sound development of China's e-commerce to be solved.In order to solve these problems,it is a good method to apply the related technology to realize the automatic response of the customer service,which can further improve the response speed and service quality of the customer service while reducing the human cost of the enterprise.This paper combs the structure of the question answering system and the existing research results,briefly describes the positioning,function and related technologies of the question answering system,completes the relevant knowledge reserves,and then analyzes several important links in the intelligent response.That is,question understanding,information retrieval,answer extraction,and sorting.According to the application areas,the question answering system can be divided into open field question answering system and closed field question answering system.The intelligent customer service system is an application of the question answering system in the closed field.Based on the requirements and related background of smart customer service system,this paper carries out research and design of smart customer service system.This article first collected a large number of customer service consulting corpus and the status of the user,after the analysis and filtering combined with common stop words to construct the corresponding stop word list,and use HIT LTP segmentation technology to deal with,build a mobile phone related professional dictionary Improve the accuracy of word segmentation,based on the existing word segmentation,word segmentation,synonym replacement and other operations,and then complete the construction of the FAQ database based on consulting corpus,and optimize the configuration of the answer based on user scenarios.After that,the keywords in the user input are extracted,word2 vec is used to find the similar words of the keywords,and it is detected whether there is a business keyword to filter,and if it does not exist,it is identified as chat,and it is transferred to the mature Turing robot API if there exists.If you do,go to the built smart customer service system.Then,according to the scene where the user is located,the content of the user's input is matched with the questions in the FAQ database.The similarity threshold is set and the optimization is performed.If the similarity is high enough,the question and answer pair of the question is directly returned;if similarity Above the set threshold,a list of questions with a higher degree of similarity is returned according to keywords,fuzzy matches,etc.,and the user selects and returns a corresponding answer;otherwise,the match fails,and it is transferred to an artificial customer service for processing.Finally,using historical consulting corpus to verify the ability of the system to answer questions,through testing can be found that this article's intelligent customer service system can meet the consumer's consulting needs to a certain extent.