A Study On Hypergraph-Based Support Methods Of Market Opportunity Discovery

The global economy makes business products or services can be easily imitated and lower barriers to entry, thus the enterprises in the dynamic market environment are required to response rapidly and shorten the innovation cycle. Finding and seizing new market opportunity has become the focus and emphasis of business decision-makers, and building support system of enterprise market opportunity discovery become the deep needs of enterprise informationization.This article is found in the summary of both domestic and international theory research and support methods, for the issues found in current study that have yet to be resolved such as non-accurate, semi-structured data sources, comlicatied relationship, flexible structure, the image of thinking, the process supporting and so on, using cognitive science analyzed the mechanism of opportunity discovery, raising new decision support models and methods based on the hypergraph theory.The basic concepts and graphics express of hypergraph are introduced. The modeling features and application fields of the hypergraph are pointed out, the current hypergraph models has been reviewed, The development network has been arranged, and the mutual relations and comparative advantages between hypergraph and other models in the application of database fields and knowledge modeling are introduced in emphasis.For opportunity discovery in non-accurate, uncertain and semi-structured environment, its mechanism is analyzed by using schema theory of cognitive science, opportunity and opportunity discovery are redefined from a cognitive point of view. Hypergraph system model of opportunity discovery is raised based on relative schema modeling to agent in hypergraph theory. Support mechanism based on hypergraph system model is designed to support data reorganization, pattern recognition, path analysis, information absorbing, schema building, as well as visualization and communication during opportunity discovery process. Comparative features and advantages of hypergraph system model to current model are analyzed.Pattern recognition being the basis of image thinking such as perceived association is clarified. Pattern recognition in opportunity discovery process is studied. various types of model primitives of hypergraph system model are defined. Frequent patterns mining algorithm in KDD is used to extract model primitives from non-accurate and semi-structured information sources, and Three-dimensional structure of schema is described based on model primitives. Two types pattern recognition in opportunity discovery is analyzed, one is based on properties, the other is based on structures. For the latter one, isomorphism determining method based on hypergraph invariants and eigenvectors is proposed.Path analysis being the basis to support opportunity for search, evaluation and interpretation is clarified. Special semantic of path analysis in opportunity discovery is defined, which means a super-path describing a feasible solution of the problem. Inadequacy of the current ultra-path algorithm is analyzed, while a super-path algorithm based on two points is proposed to solve problem of a given entity in all solution domain.Information assimilating being the basis of information exchange and schema construction is clarified, which reflects the support of hypergraph system model to the dynamic characteristics of opportunity discovery. Information assimilating, that is, as an open cognitive system, opportunity discovery interchange information with external environment, and result in schema system evolution, is special studied. Several types of relational operator in the information assimilating are described in detail. A database operation mainly based on natural connect computing is designed for Assimilate information assimilating. Schema construction and innovation based on genetic algorithm is designed for acclimation.Applications to commercial banks as the background, the hypergraph system model of commercial banks opportunity discovery are established. Based on hypergraph system model, the decision support for pattern recognition, path analysis and information absorbing is given. Compared with the current support technology and methods of opportunity discovery, the features and advantages of hypergraph system model are validated.