Open AccessFuzzy Cloud Evaluation of Service Quality Based on DP-FastText
Author(s) -
Huanzhuo Ye,
Yuan Li
Publication year - 2021
Publication title -
wseas transactions on computers
Language(s) - English
Resource type - Journals
eISSN - 2224-2872
pISSN - 1109-2750
DOI - 10.37394/23205.2021.20.16
Subject(s) - computer science , cloud computing , fuzzy logic , service (business) , service quality , data mining , quality (philosophy) , quality of service , database , artificial intelligence , computer network , philosophy , economy , epistemology , economics , operating system
This study proposes a service quality evaluation model framework which integrates automatic data acquisition, intelligent data processing and real-time data analysis with online comment data as data sources by introducing natural language processing technology based on management methods to break the traditional idea of over-reliance on human resources for service quality evaluation. The framework is mainly divided into text data preparation, fine-grained sentiment analysis and fuzzy cloud evaluation models. Data preparation module is responsible for preparing the initial data, and the fine-grained sentiment analysis module is responsible for pre-training a fine-grained sentiment classification model. The fuzzy cloud evaluation module uses the data obtained from the first two modules to evaluate service quality. By applying the model into catering industry, the feasibility of the model is proved and individuality, efficiency, dynamicity and intelligence of the model give it more advantage in the practice of service quality evaluation