Research on the Intensity of Subjective and Objective Vocabulary in Interactive Text Based on E-Learning
Based on the text subjective judgment algorithm based on the rough set, we proposed an improved logarithmic linear model and fuzzy set combining the subjective intensity of learning method Chinese words and lexical subjectivity recognition, which is appli
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Abstract Based on the text subjective judgment algorithm based on the rough set, we proposed an improved logarithmic linear model and fuzzy set combining the subjective intensity of learning method Chinese words and lexical subjectivity recognition, which is applied in the E-learning interactive text, and achieved better recognition results. Keywords Log-linear model Subjectivity intensity
Fuzzy set
E-Learning interactive text
1 Introduction With the development of network information technology, E-Learning has become an effective form of school education, enterprise training, organization training. However, the traditional E-Learning system lack of emotion generally, in order to increase the emotional functions of E-Learning system, people began to study the emotion of learners studying with E-Learning. Approaches commonly used are: facial expression recognition, text sentiment analysis, speech emotion analysis. In fact, to mine the learners’ ideas from academic texts, and then analyzed the Supported by the National Natural Science Foundation of China under No. 60970052, Beijing National Natural Science Foundation (The Study of Personalized E-learning Community Education based on Emotional Psychology 4112014). W. Wang (&) P. Li Department of Information Engineering Institute, University of Capital Normal, Beijing, China e-mail: [email protected] P. Li e-mail: [email protected]
Z. Wen and T. Li (eds.), Knowledge Engineering and Management, Advances in Intelligent Systems and Computing 278, DOI: 10.1007/978-3-642-54930-4_2, Springer-Verlag Berlin Heidelberg 2014
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psychological condition is in the premise of academic interactive text subjectivity classification [1]. Subjectivity of Chinese words is a basic problem in text sentiment analysis. Its accuracy will directly affect the follow-ups; it is the basis of the sentiment analysis of the phrase level, sentence level, and paper-level. Although many studies have done [2, 3], the existing analysis methods in dealing with large-scale texts still face the following difficulties: For example, different words in the expression of Opinion may have different subjective intensity, and thus have different effects on subjective analysis of sentences or articles. Moreover, the same words in different language environments may have different subjective intensity, a major problem we are faced is distinguish the subjectivity of words according to the current language environments, but there is less research on the words subjective intensity. Also, a subjective sentence may include two or more subjectivity of the words, but the roles they play to express their opinions are different. This article firstly introduces the rough set theory for reduction of the text, and secondly extracts corpus from E-leaning platform, and the use of rough set theory to reduce; then extracts emotional candidate words and views indicator words, and calculates their subjective weights; Finally, we combine fuzzy set theory, inspecting the impact of the intensity
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