Multi-action-based approach for constructing knowledge map

To alleviate the information overload in the product design process,this work proposes a multiaction-based method for constructing knowledge map. Since the relationships of knowledge are implicit in the collected user activities,the method calculates the similarity according to the collected user activities.Three concepts,including knowledge,action and user,are explained first. Based on this,the similarity calculation method is illustrated in detail. The dependencies of actions and relations of the user are considered in the calculation method. Further,the approach of applying the constructed knowledge map to alleviate information overload is proposed. At last,the proposed method is validated by a knowledge search and result comparison experiment.

A Domain Knowledge Driven Approach for User Interface Software Development

A domain knowledge driven user interface development approach is described.As a conceptual de- sign of the user interface,the domain knowledge defines the user interface in terms of objects,actions and their relationships that the user would use to interact with the application system.It also serves as input to a user interface management system(UIMS)and is the kernel of the target user interface. The principal ideas and the implementation techniques of the approach is discussed.The user interface model,user interface designer oriented high-level specification notation,and the transformation algorithms on domain knowledge are presented.

Object-Based Method Outperforms Per-Pixel Method for Land Cover Classification in a Protected Area of the Brazilian Atlantic Rainforest Region

Conventional image classification based on pixels hinders the possibilities to obtain information contained in images, while modern object-based classification methods increase the acquisition of information about the object and the context in which it is inserted in the image. The objective of this study was to investigate the performance of different classification methods for land cover mapping in the vicinity of the Alto Ribeira Tourist State Park, a Brazilian Atlantic rainforest area. Two classification methods were tested, including i） a hybrid per-pixel classification using the image processing software ERDAS Imagine version 9.1 and ii） an object-based classification using the software eCognition version 5. In the first method, six different classes were established, while in the second method, another two classes were established in addition to the six classes in the first method. Accuracy assessment of the classification results presented showed that the object-based classification with a Kappa index value of 0.8687 outperformed the per-pixel classification with a Kappa index value of 0.2224. Application of the user＇s knowledge during the object-based classification process achieved the desired quality; therefore, the use of inter-relationships between objects, superelasses, subclasses, and neighboring classes were critical to improving the efficiency of land cover classification.