异构数据库之间的格式转换

异构数据库之间的格式转换＠杜志典＠徐廷伟异构数据库之间的格式转换＊杜志典徐廷伟（计算中心）当前，随着网络技术与数据库技术的发展，各单位都需要建立大型数据库管理系统，以满足日益增长的业务需求．为了保护已有投资，常常需要将已开发的Ｆｏｘｐｒｏ数据库系统集成到以...     

An Efficient Algorithm for Discovering Co-occurrence Concepts Through Pathfinder Paradigm

The Pathfinder paradigm has been used in generating and analyzing graph models that support clustering similar concepts and minimum-cost paths to provide an associative network structure within a domain. The co-occurrence pathfinder network （ CPFN ） extends the traditional pathfinder paradigm so that co-occurring concepts can be calculated at each sampling time. Existing algorithms take O（n（s）） time to calculate the pathfinder network （PFN） at each sampling time for a non-completed input graph of a CPFN （r = ∞, q = n - 1）, where n is the number of nodes in the input graph, r is the Minkowski exponent and q is the maximum number of links considered in finding a minimum cost path between vertices. To reduce the complexity of calculating the CPFN, we propose a greedy based algorithm, MEC（G） algorithm, which takes shortcuts to avoid unnecessary steps in the existing algorithms, to correctly calculate a CPFN （r = ∞, q= n - 1） in O（klogk） time where k is the number of edges of the input graph. Our example demonstrates the efficiency and correctness of the proposed MEC（G） algorithm, confirming our mathematic analysis on this algorithm.