Yinglin Wang

Ontology-based reconfigurable case-based reasoning system for knowledge integration

Cased-based reasoning (CRB) is a methodology that follows mankinds problem solving strategy. Most traditional CBR systems are built in a fixed index structure and they cannot be easily adapted to fit new environment. In this paper a KM framework is proposed that combines ontology, case templates and case-based reasoning to solve the problems. In this framework, enterprise ontology provides the basis for integration among knowledge resources. Case templates can be reconfigured based on the enterprises ontology by the user. The knowledge structure and the user-interfaces of the system knowledge structure and the user-interface of the system can be reconfigured so that the system can suit for an enterprise whose knowledge structure and the requirement for knowledge management system change rapidly. Besides, a workflow based knowledge acquisition method is also discussed that assures the quality of the knowledge acquired.

An ontology-based framework for building adaptable knowledge management systems

A framework of an adaptive knowledge management system is put forward. While the invariable infrastructure of the framework is coded in the system, the other user-specific features are supposed to be customized or defined later in the deployment phase by the end users. Moreover, a model for integrating the knowledge management process and the business process is presented. In this model, three spaces, i.e., the task space, the knowledge space and the process space, are proposed. The relationships of these spaces and the functions of the integrated system are discussed. Based on the framework, a system named ReKM has been developed and deployed in enterprises.

A collaborative knowledge production model for knowledge management in complex engineering domains

Knowledge management (KM) has recently been considered as an important strategy for an enterprise to maintain competence in the fierce market competition. Yet the tools of building lifecycle knowledge management systems are not mature. In this paper we study the issues of how to collect and evaluate knowledge in a collaborative team of a complex engineering domain. We provide a collaborative knowledge production model for it by combining case based knowledge management and workflow management techniques. In this model, we regard knowledge as specific type of product that is made up of several components, which are usually produced by different employees or branches in an enterprise. Each knowledge item has several kinds of statuses to mark its stage in the production process. Each knowledge process changes the status of knowledge items that are being produced. To facilitate reconfiguration, the system is divided into several modules that can be defined separately by users with the minimal influence to other modules.

The crowd framework for multiobjective particle swarm optimization

Multiobjective particle swarm optimization meets two difficulties—guiding the search towards the Pareto front and maintaining diversity of the obtained solutions—so a great number of improvements are possible. Our crowd framework systematically summarizes these improvements, extracts them into reusable strategies and categorizes them into modules by their optimization mechanisms. We introduce a number of new techniques within the modules. Strategies are compared first theoretically and then practically through amended ZDT series. We propose a sequence for module application based on the correlation between the modules. The resulting algorithms give incredible performance. Thus our crowd framework forms a new baseline for MOPSO.

MULTIOBJECTIVE PARTICLE SWARM OPTIMIZATION BASED ON DIMENSIONAL UPDATE

For multiobjective particle swarm optimization (MOPSO), two particles may be incomparable, i. e., not dominated by each other. The personal best and the global best for the particle become less optimal, thus the convergence becomes slow. Even worse, an archive of a limited size can not cover the entire region dominated by the Pareto front, the uncovered region can contain unidentifiable nondominated solutions that are not optimal, and thus the precision the algorithm achieves encounters a plateau. Therefore we propose dimensional update, i. e., evaluating the particles fitness after updating each variable of its position. Separate consideration of the impact of each variable decreases the occurrence of incomparable relations, thus improves the performance. Experimental results validate the efficiency of our algorithm.

A Framework for GPS/INS based Portable Positioning System

In this paper, we describe a framework for GPS/INS based Portable Positioning System. The framework includes two main components: receiving terminal and monitoring center. In the receiving terminal, the digital compass and the GPS modules are both connected with an I/O interface in a FPGA to provide an integrated positioning solution. This integrated positioning algorithm can solve the problems arising both in standalone modes and in traditional integrated measurements. In the monitoring center, several improvements have been discussed to ensure runtime efficiency and the robustness of the PPS. The experimental results from two positioning modes validate the effectiveness of the proposed algorithm.

Ontology based unstructured text query

This paper describes an approach that offers a more general and easier way to access the knowledge repository as a useful part of a knowledge management system. The approach applies a domain ontology in the query text analysis and ontology mapping technique in the knowledge search process. It sets up relationship between the query text in unstructured natural language expressions and the instances in the knowledge base to find those instances that match the condition expressed by the query most. The application magnifies the scope of ontology, and promotes the applicability of ontology-based system.

Formalizing mobile agent system model based on ontology

From the view of distributed application, it has the two important points to build ontology: sharing domain knowledge, reuse of domain knowledge. There are some problems in the present distributed applications based on ontology: It may use different terms for a same concept in different systems and it does not facilitate the information interchange between heterogeneous systems. Also, it lacks of a rigorous formal logic description for verification. Considering the application in the Internet, in this paper, we present a uniform expression format based on XML/RDF to describe the ontology, and extend PSL by creating new PSL Extensions to define the ontology of location, organization, resources, activity, process and product. These provide the mobile agent application system formal description language that supports the verification of the system and the translation with other application systems.

A case study of an inter-enterprise workflow-supported supply chain management system

Doing business over the Internet is very cheap and convenient, which enlarges the view of enterprises and lets the enterprises have more chances to select their partners. To achieve these goals, we need the support of information systems, in which workflow management system is of significance. The inherent characteristics of a workflow system make it suitable to implement the cross organization management. Nowadays, however, workflow systems which support cross organization management are not common. When developing a supply chain management system for a big motorcycle corporation in China, we have to construct an inter-enterprise workflow architecture over Internet by ourselves. The main part of the architecture is a workflow-supported inner supply chain system and an integrated interface, through which the whole supply chain system cross several independent enterprises is built and the information exchange is fulfilled. This paper presents how the system is designed and implemented in detail as well as the experiences and lessons gained.