Title :
Measuring Knowledge Delivery Quantity of Associated Knowledge Flow
Author :
Zhang, Shunxiang ; Luo, Xiangfeng ; Chen, Jinjun ; Xu, Zheng ; Yu, Jie ; Xu, Weimin
Author_Institution :
Joint Lab. of Next-Generation Internet Interactive Comput., Shanghai Univ., Shanghai, China
Abstract :
Associated knowledge flow (AKF) is a sequential link between associated topics, which can be applied to intelligent browsing and personalized recommendation. One key problem is how to measure the knowledge delivery quantity (KDQ) on an AKF. In this paper, a computational method of knowledge delivery quantity on an AKF is proposed. Firstly, considering the keywords and associated relations between two nodes, four key factors for knowledge delivery quantity between two nodes are investigated. Secondly, based on the four factors, an algorithm is proposed to calculate the knowledge delivery quantity between two nodes. Thirdly, the knowledge delivery quantity of a node with adjacent nodes is calculated for the measurement of local knowledge delivery on an AKF. Lastly, according to the local knowledge delivery, the average knowledge delivery quantity is proposed to measure an AKF. Experimental results show that the proposed measurement method is accurate and effective.
Keywords :
data mining; associated knowledge flow; intelligent browsing; knowledge delivery quantity; knowledge discovery; personalized recommendation; sequential link; Computational intelligence; Data models; Fluid flow measurement; Fuzzy cognitive maps; Grid computing; Internet; Knowledge management; Resource management; Technological innovation; Web services; Associated knowledge flow; associated relations; knowledge delivery quantity;
Conference_Titel :
Semantics, Knowledge and Grid, 2008. SKG '08. Fourth International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-0-7695-3401-5
Electronic_ISBN :
978-0-7695-3401-5
DOI :
10.1109/SKG.2008.92
