Use Semantic Analysis to Improve the Performance of Help Desk Problems

Abstract

With the increasing popularity and importance of information systems in enterprises in order to reduce the negative impact of the high turnover rate of Help Desk personnel who specialize in information-related issues and improve the efficiency of enterprises text analysis methods are used to record the history of problem-solving systems It is worth investing in the collection of valuable reusable information In order to analyze the semantic relationship this study uses the E-HowNet semantic knowledge base to convert the semantic relationship of Chinese vocabulary and then uses the topic model LDA method to find out the topic represented by each article and gather similar questions according to the topic The answer records of these questions are taken out and the abstracts are extracted and presented to the users according to the topic relevance After the verification the precision of the conversion of semantic meanings into the complete part of speech screening is improved by 8 5% than the no semantic processing The LDA-trained topic model takes the same subject problem to calculate Although precision is reduced from 99% to 92% the time spent can be shortened to the original 1/34 and the study essay belongs to the short essay so the threshold of sentence relevance should not be set too high to avoid the abstract extraction failure In addition it is found that the summary effect of AP Cluster is better than K-means

Date of Award	2019
Original language	English
Supervisor	Hei-Chia Wang (Supervisor)