This paper proposes the principle of comprehensive knowledge discovery. Unlike most of the current knowledge discovery methods, the comprehensive knowledge discovery considers both the spatial relations and attributes...This paper proposes the principle of comprehensive knowledge discovery. Unlike most of the current knowledge discovery methods, the comprehensive knowledge discovery considers both the spatial relations and attributes of spatial entities or objects. We introduce the theory of spatial knowledge expression system and some concepts including comprehensive knowledge discovery and spatial union information table (SUIT). In theory, SUIT records all information contained in the studied objects, but in reality, because of the complexity and varieties of spatial relations, only those factors of interest to us are selected. In order to find out the comprehensive knowledge from spatial databases, an efficient comprehensive knowledge discovery algorithm called recycled algorithm (RAR) is suggested.展开更多
Courtroom interpreting has now attracted more attentions due to the fast growth of interpreting as a profession and the development of globalization. Courtroom interpreting is different from other interpreting modes i...Courtroom interpreting has now attracted more attentions due to the fast growth of interpreting as a profession and the development of globalization. Courtroom interpreting is different from other interpreting modes in that it involves both legal knowledge and interpreting capability. Misinterpreting in courtroom can pose a threat to the human rights and sometimes can be a matter of life and death. This paper discusses some common challenges faced by courtroom interpreters and proposes coping tactics guided by ethical principles展开更多
The teachers use explicit learning in the traditional teaching of English grammar, which pays great attention to the master of grammar knowledge points. Nowadays, some English teachers excessively emphasize the import...The teachers use explicit learning in the traditional teaching of English grammar, which pays great attention to the master of grammar knowledge points. Nowadays, some English teachers excessively emphasize the importance of teaching grammar imperceptibly, but neglect to explain the rules of grammar. The diametrically isolation of implicit and explicit learning doesn＇t correspond with the English grammar teaching. So the teachers should combine the two learning styles in order to make the best use of them to teach English grammar.展开更多
Data analysis and automatic processing is often interpreted as knowledge acquisition. In many cases it is necessary to somehow classify data or find regularities in them. Results obtained in the search of regularities...Data analysis and automatic processing is often interpreted as knowledge acquisition. In many cases it is necessary to somehow classify data or find regularities in them. Results obtained in the search of regularities in intelligent data analyzing applications are mostly represented with the help of IF-THEN rules. With the help of these rules the following tasks are solved： prediction, classification, pattern recognition and others. Using different approaches---clustering algorithms, neural network methods, fuzzy rule processing methods--we can extract rules that in an understandable language characterize the data. This allows interpreting the data, finding relationships in the data and extracting new rules that characterize them. Knowledge acquisition in this paper is defined as the process of extracting knowledge from numerical data in the form of rules. Extraction of rules in this context is based on clustering methods K-means and fuzzy C-means. With the assistance of K-means, clustering algorithm rules are derived from trained neural networks. Fuzzy C-means is used in fuzzy rule based design method. Rule extraction methodology is demonstrated in the Fisher＇s Iris flower data set samples. The effectiveness of the extracted rules is evaluated. Clustering and rule extraction methodology can be widely used in evaluating and analyzing various economic and financial processes.展开更多
基金theChina’sNationalSurveyingTechnicalFund (No .2 0 0 0 7)
文摘This paper proposes the principle of comprehensive knowledge discovery. Unlike most of the current knowledge discovery methods, the comprehensive knowledge discovery considers both the spatial relations and attributes of spatial entities or objects. We introduce the theory of spatial knowledge expression system and some concepts including comprehensive knowledge discovery and spatial union information table (SUIT). In theory, SUIT records all information contained in the studied objects, but in reality, because of the complexity and varieties of spatial relations, only those factors of interest to us are selected. In order to find out the comprehensive knowledge from spatial databases, an efficient comprehensive knowledge discovery algorithm called recycled algorithm (RAR) is suggested.
文摘Courtroom interpreting has now attracted more attentions due to the fast growth of interpreting as a profession and the development of globalization. Courtroom interpreting is different from other interpreting modes in that it involves both legal knowledge and interpreting capability. Misinterpreting in courtroom can pose a threat to the human rights and sometimes can be a matter of life and death. This paper discusses some common challenges faced by courtroom interpreters and proposes coping tactics guided by ethical principles
文摘The teachers use explicit learning in the traditional teaching of English grammar, which pays great attention to the master of grammar knowledge points. Nowadays, some English teachers excessively emphasize the importance of teaching grammar imperceptibly, but neglect to explain the rules of grammar. The diametrically isolation of implicit and explicit learning doesn＇t correspond with the English grammar teaching. So the teachers should combine the two learning styles in order to make the best use of them to teach English grammar.
文摘Data analysis and automatic processing is often interpreted as knowledge acquisition. In many cases it is necessary to somehow classify data or find regularities in them. Results obtained in the search of regularities in intelligent data analyzing applications are mostly represented with the help of IF-THEN rules. With the help of these rules the following tasks are solved： prediction, classification, pattern recognition and others. Using different approaches---clustering algorithms, neural network methods, fuzzy rule processing methods--we can extract rules that in an understandable language characterize the data. This allows interpreting the data, finding relationships in the data and extracting new rules that characterize them. Knowledge acquisition in this paper is defined as the process of extracting knowledge from numerical data in the form of rules. Extraction of rules in this context is based on clustering methods K-means and fuzzy C-means. With the assistance of K-means, clustering algorithm rules are derived from trained neural networks. Fuzzy C-means is used in fuzzy rule based design method. Rule extraction methodology is demonstrated in the Fisher＇s Iris flower data set samples. The effectiveness of the extracted rules is evaluated. Clustering and rule extraction methodology can be widely used in evaluating and analyzing various economic and financial processes.
