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Design And Implement A Teaching Evaluation System Of Yantai University Based On Text Opinion Mining Technology

Posted on:2016-03-23Degree:MasterType:Thesis
Country:ChinaCandidate:R W LiangFull Text:PDF
GTID:2308330473452253Subject:Software engineering
Abstract/Summary:PDF Full Text Request
With the popularization of higher education, the guarantee and the improvement of the education quality of education have already become the center of the development of higher education..Students’ evaluation of teaching as an important part of teaching quality guarantee and increase of, has been gradually in the implementation, to improve the effectiveness and scientificalness of evaluation results has become the important task of college teachers and administrators pay attention to.This system takes the real data of students from Yantai University as the object of study, and carries on the text mining to the subjective message in the students’ evaluation.. Firstly 3GWS software to subjective message segmentation, appraise dictionary based on HowNet and application of text automatic summarization, the importance of attribute technology, using the statistical analysis algorithm and recursive grammar decline analysis method, to online assessment training data for in-depth research and analysis, the final obtained can reflect the teaching quality of the teachers a series of objective and fair and effective data. The system includes four functions: modeling, preprocessing, statistical analysis, automatic summarization, result and so on. Among them, the algorithm of segmentation and weight calculation is used..The successful implementation of the system, will greatly enhance the scientific and effective evaluation results, to improve the enthusiasm of the teachers’ teaching work, continuous improvement of teaching methods, to improve the level of college teaching management, to guarantee and improve the quality of education and teaching has important significance.
Keywords/Search Tags:Data Mining, Teaching evaluating, Automatic summarization, Feature extraction
PDF Full Text Request
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