Research of Text Topic Automatic Extraction Method Based on Rough Set Theory

On the base of researching currently popular text topic extraction technologies, a new text topic automatic abstracting method is proposed based on rough set theory and rough similarity. Firstly it separated a text into words and sentences to complete information segmentation, and then constructed a similarity matrix by computing the rough similarity between different words to realize the text clustering, finally extracted representative sentences from each class to generate the text topic. The experiment shows that the method is feasible and effective.

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An Improved Method for the Feature Extraction of Chinese Text by Combining Rough Set Theory with Automatic Abstracting Technology

Communications in Computer and Information Science - Contemporary Research on E-business Technology and Strategy ◽

10.1007/978-3-642-34447-3_44 ◽

2012 ◽

pp. 496-509 ◽

Cited By ~ 1

Author(s):

Min Shen ◽

Baosen Dong ◽

Linying Xu

Keyword(s):

Feature Extraction ◽

Set Theory ◽

Rough Set ◽

Chinese Text ◽

Rough Set Theory ◽

Improved Method ◽

Automatic Abstracting

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INCLUSIVENESS MEASUREMENT OF RANDOM EVENTS USING ROUGH SET THEORY

International Journal of Uncertainty Fuzziness and Knowledge-Based Systems ◽

10.1142/s0218488507004807 ◽

2007 ◽

Vol 15 (04) ◽

pp. 483-491

Author(s):

H. TORABI ◽

B. DAVVAZ ◽

J. BEHBOODIAN

Keyword(s):

Set Theory ◽

Rough Set ◽

Rough Set Theory ◽

Probability Model ◽

Complete Information ◽

Random Events ◽

Arbitrary Event ◽

Upper Probability ◽

Lower And Upper Probability

In some probabilistic problems, complete information about the probability model may not exist. In this article, we obtain a lower and upper probability for an arbitrary event by using rough set theory and then a measurement for inclusiveness of events is introduced.

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Extraction method of decision rules for turbine-generator unit fault diagnosis based on rough set theory

Fifth World Congress on Intelligent Control and Automation (IEEE Cat. No.04EX788) ◽

10.1109/wcica.2004.1343700 ◽

2004 ◽

Cited By ~ 1

Author(s):

Wentao Huang ◽

Xuezeng Zhao ◽

Weijie Wang ◽

Lizhou Dai

Keyword(s):

Fault Diagnosis ◽

Set Theory ◽

Rough Set ◽

Extraction Method ◽

Rough Set Theory ◽

Decision Rules ◽

Turbine Generator ◽

Generator Unit

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Decision rule extraction method based on rough set theory and fuzzy set theory

2005 International Conference on Machine Learning and Cybernetics ◽

10.1109/icmlc.2005.1527312 ◽

2005 ◽

Author(s):

Ming-Chun Wang ◽

Zheng-Ou Wang ◽

Ming Zhang ◽

Peng Yan

Keyword(s):

Decision Rule ◽

Set Theory ◽

Rough Set ◽

Fuzzy Set ◽

Fuzzy Set Theory ◽

Extraction Method ◽

Rough Set Theory ◽

Rule Extraction

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Study on decision-making of soccer robot based on rough set theory

Interaction Studies ◽

10.1075/is.18020.zha ◽

2019 ◽

Vol 20 (1) ◽

pp. 61-77

Author(s):

Li Zhang ◽

Xulu Xue

Keyword(s):

Decision Making ◽

Set Theory ◽

Rough Set ◽

Imperfect Information ◽

Rough Set Theory ◽

Decision Rules ◽

Complete Information ◽

Uncertain Information ◽

Soccer Robot ◽

Decision Making System

Abstract “Rough set” is a theory put forward by the polish scholar Z. Pawlak, which is a useful mathematics tool for dealing with vague and uncertain information. Rough set theory can achieve a subset of all attribute which preserves the discernible ability of original features, by using the data only with no additional information. As a typical system of multi-agent, the decision-making system of soccer robot has the features of multi-layered, antagonism, and cooperation. On the bases of rough set theory, this paper established a decision making system with complete information for soccer robot, and then reduce the condition and decision attributes and their values, to get the simply decision rules. On the otherwise, considering the situation of information loss, we study decision making of imperfect information system, extract the decision rules and calculate the reliability, so that the rules can assist the agent to make right decision in competition. The simulation result shows that the algorithm is correct and effective.

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