Research On Ontology Based Proactive Knowledge System And Its Key Tchenologies

How to gain and utilize knowledge is one of critical aspects for enterprises to preserve competitive power. The study in the thesis aims at the problems which exist in knowledge utilization in the knowledge intensive enterprises. Some key techniques of proactive knowledge system are studied deeply with the application of knowledge engineering and ontology theory method. The framework of Ontology based Proactive Knowledge System(Ontology based Proactive Knowledge System,OPKS)is proposed and some key techniques, such as, user knowledge requirement,ontology mapping,ontology evolution,global query, are studied. The system prototype is constructed finally.Main contributions of this thesis are the following:(1) OPKS framework is proposed.The user knowledge requirement is taken as the driving factor and ontologies are used to describe knowledge in OPKS. Ontology mapping is ultilized to interoperate knowledge sources. Proper knowledge may be provided to the user based on the user knowledge requirement in OPKS. It effectively helps to reduce the difficulty for the user to seek knowledge.(2)The user knowledge requirtment model and its related algorithms are proposed.Decisive factors of user knowledge requirement are described by the user knowledge requirtment model. Not only business task, but also user personalization characteristic are considered. Related algorithms of the user knowledge requirement model include user knowledge requirement generation algorithm and user knowledge hybrid evolution algorithm. The user knowledge requirement are automatically produced by the user knowledge requirement generation algorithm based on the user knowledge requirement model. The user knowledge hybrid evolution algorithm includes the user knowledge real-time evolution algorithm and the user knowledge stage evolution algorithm. User knowledge change after the user read recommended knowledge sources is processed by the user knowledge real-time evolution algorithm. The user's knowledge forgetting is reflected by the user knowledge stage evolution algorithm(3) One kind of ontology semantic mapping algorithm is proposed. What is returned by the algorithm is not similarity coefficients but semantic relations. Semantic relations are determined through comparing attribute sets. Ontology semantic information is taken into account adequately while computing concepts similarity. Semantic radius are used to control the scope of related concepts.(4) Ontology evolution method based on user defined change is proposed.The user can formulate different granularity of ontology change by combining ontology atomic changes into user defined change. It increases the flexibility of user change expression.The optimization of user defined change can reduce executing time of change sequence.(5) The algorithms of decomposition and translation are proposed to query heterogeneous knowledge sources.The input RDQL query is decomposed into sub-queries specific to different knowledge sources in global query decomposition algorithm based on ontology semantic mapping.Query translating algorithms of RDQL-SQL and RDQL-XQuery can translate RDQL to SQL and XQuery,respectively.(6) OPKS prototype is constructed.OPKS prototype is constructed based on Web Service.UML is used to analyze and design the system.System use case diagrams,class diagrams and sequence diagrams are established.System implementation is specified.