Learning Machine, Vietnamese Based Human-Computer Interface.
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| Title: | Learning Machine, Vietnamese Based Human-Computer Interface. |
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| Language: | English |
| Authors: | Northwest Regional Educational Lab., Portland, OR. |
| Peer Reviewed: | N |
| Page Count: | 62 |
| Publication Date: | 1998 |
| Document Type: | Reports - Descriptive Speeches/Meeting Papers |
| Descriptors: | Algorithms, Character Recognition, Color, Educational Technology, Foreign Countries, Human Factors Engineering, Information Technology, Knowledge Base for Teaching, Machine Translation, Mathematics, Optical Scanners, Programming, Vietnamese, Word Recognition |
| Abstract: | The sixth session of IT@EDU98 consisted of seven papers on the topic of the learning machine--Vietnamese based human-computer interface, and was chaired by Phan Viet Hoang (Informatics College, Singapore). "Knowledge Based Approach for English Vietnamese Machine Translation" (Hoang Kiem, Dinh Dien) presents the knowledge base approach, which consists of concepts such as things, actions, relations, and attributes, organized on the structure of inheritance hierarchy. "A Learning Algorithm for Feature Selection Based on Genetic Approach" (Nguyen Dinh Thuc, Le Hoai Bac) presents a genetic algorithm that chooses relevant features from a set of given features, for feature selection based on the correlation among the features and between every feature and given target curve. "Artificial Neural Network for Color Classification" (Tran Cong Toai) examines several neural network models, their learning schemes, and their effectiveness in color classification. "Synthesizing and Recognizing Vietnamese Speech" (Hoang Kiem, Nguyen Minh Triet, Vo Tuan Kiet, Thai Hung Van, Luu Duc Hien, Bui Tien Len) presents algorithms applied successfully in Vietnamese isolated word recognition and Vietnamese synthesis. "On-Line Character Recognition" (Nguyen Thanh Phuong) presents a real-time handwriting character recognition system based on a structural approach. "Data Mining and Knowledge Acquisition from a Database" (Hoang Kiem, Do Phuc) considers how to use multi-dimensional data model (MDDM) for mining rules in a large database. "Genetic Algorithm for Initiative of Neural Networks" (Nguyen Dinh Thuc, Tan Quang Sang, Le Ha Thanh, Tran Thai Son) describes a procedure for initiative of neural networks based on genetic algorithms, based on the correlation between every weight and error function. (SWC) |
| Entry Date: | 1998 |
| Accession Number: | ED417708 |
| Database: | ERIC |
| Abstract: | The sixth session of IT@EDU98 consisted of seven papers on the topic of the learning machine--Vietnamese based human-computer interface, and was chaired by Phan Viet Hoang (Informatics College, Singapore). "Knowledge Based Approach for English Vietnamese Machine Translation" (Hoang Kiem, Dinh Dien) presents the knowledge base approach, which consists of concepts such as things, actions, relations, and attributes, organized on the structure of inheritance hierarchy. "A Learning Algorithm for Feature Selection Based on Genetic Approach" (Nguyen Dinh Thuc, Le Hoai Bac) presents a genetic algorithm that chooses relevant features from a set of given features, for feature selection based on the correlation among the features and between every feature and given target curve. "Artificial Neural Network for Color Classification" (Tran Cong Toai) examines several neural network models, their learning schemes, and their effectiveness in color classification. "Synthesizing and Recognizing Vietnamese Speech" (Hoang Kiem, Nguyen Minh Triet, Vo Tuan Kiet, Thai Hung Van, Luu Duc Hien, Bui Tien Len) presents algorithms applied successfully in Vietnamese isolated word recognition and Vietnamese synthesis. "On-Line Character Recognition" (Nguyen Thanh Phuong) presents a real-time handwriting character recognition system based on a structural approach. "Data Mining and Knowledge Acquisition from a Database" (Hoang Kiem, Do Phuc) considers how to use multi-dimensional data model (MDDM) for mining rules in a large database. "Genetic Algorithm for Initiative of Neural Networks" (Nguyen Dinh Thuc, Tan Quang Sang, Le Ha Thanh, Tran Thai Son) describes a procedure for initiative of neural networks based on genetic algorithms, based on the correlation between every weight and error function. (SWC) |
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