Knowledge Reuse Enhancement with Motional Visual Representation

Abstract

The growing complexity of information and documents has made it difficult for knowledge receivers to understand digital contents; therefore, multiple knowledge representation schemes are required for enterprise knowledge services. Traditional schemes for explicit knowledge representation within enterprise and academic circles are primarily text oriented, and thus, a great deal of time and effort is required for knowledge receivers to understand the contents, especially for motion knowledge. In order to enhance knowledge reuse with motion knowledge extraction, representation, and visualization, this research focuses on the development of a motion knowledge representation and visualization (MKRV) model for Chinese documents with three modules, namely, the automatic thesaurus definition (ATD) module, the target sentence extraction and formatting (TSEF) module, and the motion knowledge visualization (MKV) module. Moreover, based on the proposed model, a motion knowledge representation and management system (MKRMS) is established. A real-world case of computer assembly is also applied in order to verify the feasibility of the proposed model. The verification results show that the system could achieve a high-performance level with a small amount of training data. As a whole, this research provides a knowledge representation and visualization approach to facilitate knowledge receivers to efficiently and accurately acquire the contents of motion knowledge. The proposed model can be applied in enterprise e-training and knowledge management systems to enhance reuse of domain knowledge.

Discover Information and Knowledge from Websites Using an Integrated Summarization and Visualization Framework

“…Some words in the results may not come from the original content directly as they could have been referred to groups of related words provided from other sources [5]. In addition, these techniques can be mixed or integrated to produce more useful summaries such as combining natural language processing and statistical approach [6] [7].…”

Summarizing information from Web sites on distributed power generation and alternative energy development

“…NLP attempts to understand and process human languages by extracting key phrases of the original text [13]. It can also be applied with machine learning using both supervised and unsupervised learning approaches.…”

iWISE, an intelligent Web Interactive Summarization Engine

“…It can work in a pre-processing stage for extracting key phrases and indentify them with respect to related domain [2]. Some tasks on natural language processing have similar characteristics of Information extraction (IE) [3].…”