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Feature selection is a very important step in text classification, which affects the accuracy and validity in text classification. Base on four classic feature selection algorithms of text mining, this paper has established a kind of integrated learning algorithm which applies with feature selection in text classification, in order to improve the accuracy of text classification. Test results show...
Web text mining is a growing research area in data mining. Interestingly, the existing Web text mining algorithms have concentrated on finding frequent patterns while discarding the less frequent ones that may contain outliers. In addition, the domain knowledge in one industry is partly different from that in the others. Whatever they belong to, web texts are analyzed using the same dictionary. This...
With the maturity of Web2.0, information exchange and information sharing have reached an unprecedented breadth and depth, which also provide a good condition for the spreading of false information in virtual communities. Through the collection and analysis of a large number of comments of virtual communities, this paper presents a solution of credibility analysis of comments of virtual community...
This paper is based on virtual community, using the cohesion subgroup analysis method to analyze the characteristics of members. The result is that the members of virtual community can be divided into large subgroups and small subgroups, large subgroups has a higher influence on the depth of knowledge exchange and diffusion and the small subgroups has a higher influence on the exchange of knowledge...
Concept Map, as a knowledge representation and knowledge organization tool, is the visual expression of the concepts and the relationships between in a certain domain. It can not only integrate tacit knowledge, but also cluster explicit knowledge. Therefore, it is important to research how to construct concept maps. This paper first analyzes the general construction method of the concept map. On this...
Knowledge Acquisition is the research hotspot in Knowledge Engineering. Its application is very wide in the intelligent system. It can be realized through the manual, semi-automatic and automatic patterns. This paper mainly discusses the realization principles of Knowledge Acquisition and its application in Intelligent Retrieve.
In order to adapt to the development tendency of knowledge organization and resolve the problem about the low efficiency of information retrieve, knowledge retrieve as a new retrieval theory is proposed. Based on the knowledge organization, it realizes the intelligent retrieve of knowledge correlation and concept semantic retrieve. It synthetically applies many new theories and technologies, such...
Because of the semantic gap between low-level feature and high-level semantic feature of images, the results of the traditional color-based image retrieval canpsilat meet userspsila needs. In order to eliminate interference factors in the image retrieval, use image semantic feature and improve the accuracy of image retrieval, the paper introduces an algorithm based on the color correlation mining...
Since the point that knowledge organizational system must be introduced into digital library was proposed, it has triggered a great concern to knowledge organization in digital library at home and abroad. This paper is based on the point, and puts forward the knowledge construction mode based on visualization e-learning. The main idea is that the learners utilize knowledge visualization tool to continually...
Considering the lack of visualization technology applications and e-learning in the current digital library construction, a visualization knowledge acquisition and knowledge innovation prototype system is designed in the paper. The visualization display and visualization mapping are used in the prototype system, and it realizes a complete knowledge chain from information extraction, knowledge acquisition,...
Semantic web service, with semantic information being added into traditional web service descriptions, can make computers understand contents on the web automatically, thereby supporting the auto-discovery, implementation, monitoring and composition of web services. OWL-s is the description language of semantic web services, but it did not provide a detailed definition for Qos (Quality of service)...
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