Process-oriented field knowledge extraction and push system and method

Abstract

A process-oriented field knowledge extraction and push system and a process-oriented field knowledge extraction and push method are provided. The process-oriented field knowledge extraction and push system includes a user module, a knowledge resource module, a knowledge push module and a process module. The process-oriented field knowledge extraction and push method comprises the following steps that: knowledge is extracted from knowledge resources and is represented by knowledge vectors, and process vectors are extracted from a process task, and user attribute vectors are extracted from user description; matching calculation is performed among the process vectors, the user attribute vectors and the knowledge vectors so as to obtain the correlation between knowledge requirement and knowledge; a knowledge scoring value can be calculated through user behavior variables; and finally, the knowledge scoring value is utilized to correct the result of knowledge correlation calculation so as to obtain a knowledge ranking result which is closely related with the process task, and more accurate push of the knowledge to the process task can be realized. According to the process-oriented field knowledge extraction and push system and the process-oriented field knowledge extraction and push method of the invention, the nature of knowledge push is defined as transmission of right knowledge to right people in a right form and in right time. The process-oriented field knowledge extraction and push system and the process-oriented field knowledge extraction and push method are advantageous in high work efficiency and high accuracy.

Description

technical field [0001] The invention relates to a computer knowledge application system, in particular to a method and a system for extracting knowledge related to user business activities and intelligently pushing the knowledge to related business activities according to actual needs. Background technique [0002] In the knowledge-based economy environment, knowledge is becoming the most important resource of more and more enterprises. The essence is to regard knowledge as the most important enterprise resource. Through knowledge acquisition and sharing, appropriate knowledge is passed on to appropriate users, thereby Effectively improve the utilization rate of enterprise knowledge, promote the knowledge innovation of employees, and enable enterprises to gain competitive advantages. [0003] Knowledge management and integration are effective means to improve the level of corporate knowledge reuse, prevent knowledge loss, and realize business process automation and intellige...

AI Technical Summary

Problems solved by technology

For the process-based knowledge push system, it mainly conducts systematic research on its theory, framework and application; for the knowledge push technology, it mainly introduces the post-oriented operation knowledge and employee-oriented project knowledge push methods; but still does not consider the knowledge field. Influenced by it, its method has the problems of large amount of retrieved data and low push accuracy; in the literature: Chen Hao, Liu Nian, Hu Yanjun wrote a paper: Research on Knowledge Modeling Based on Workflow, published in "Manufacturing Automation", 2005, 27 (5): 8-12, proposed workflow-based knowledge modeling and its system framework, discussed the integration technologies supporting knowledge and knowledge, knowledge and people, and knowledge and process, and applied knowledge to business processes of enterprises method; but this article only considers the interaction between workflow and knowledge base, and does not consider the influence of knowledge subject—people in it, and only establishes a conceptual model and briefly introduces related technologies

The common disadvantage of the above studies is that the proposed knowledge matching and push method has problems such as low efficiency and poor accuracy.

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