Huiying Gao

Web Services Classification Based on Intelligent Clustering Techniques

The better way for Web services discovery is to classify the Web services into different categories when they are published in a registry. The method of intelligent clustering based classification of the Web services is mainly studied. A hybrid solution is proposed for building and populating a taxonomy structure by combining human knowledge with the techniques of artificial intelligence. The Web service is converted into standard vector format through Web service description language (WSDL) document. The self-organizing neural network based learning algorithm and clustering algorithm are designed and implemented to classify the Web services automatically.

On Dynamic Agility of Inter-Organizational Processes

The agility of inter-organizational process represents the ability of virtual enterprise to respond rapidly to the changing market environment. Many theories and methodologies about inter-organizational process have been developed but the dynamic agility has seldom been addressed. A virtual enterprise whose process has a high dynamic agility will be able to adjust with the changing environment in short time and low cost. This paper analyzes the agility of inter-organizational process from a dynamic perspective. Two indexes are proposed to evaluate the dynamic agility: time and cost. Furthermore, the method to measure the dynamic agility using simulation is studied. Finally, a case study is given to illustrate the method to measure the dynamic agility.

Ontology-based Enterprise Content Retrieval Method

As the traditional way of information retrieval is based on keywords that the computer cannot understand users’ potential semantic and personalized query requirements, an ontology-based method of the enterprise content retrieval is studied in this paper. The architecture of the ontology-based enterprise content retrieval model is proposed and the retrieval process is discussed. Take the electronic products distributing company as an example, the enterprise ontology is set up and an ontology-based semantic retrieval algorithm is designed, which provides a reference for content retrieval in the enterprises.

Service-Oriented Modeling Method for the Development of an E-Commerce Platform

In order to realize the reusability and flexibility of the information system and to easily integrate it with other systems, a service-oriented modeling method is mainly studied based on IBM-SOMA methodology together with UML, object-oriented method and component technologies. The methods lifecycle consists of requirement analysis, service-oriented analysis, and service-oriented design. The activities of each phase are illustrated by the following example: the development of an e-commerce platform to provide the guidelines and references to the new development of service-based system.

Hierarchical Clustering Based Web Service Discovery

This paper presents a hierarchical clustering method for semantic Web service discovery. This method aims to improve the accuracy and efficiency of the traditional service discovery using vector space model. The Web service is converted into a standard vector format through the Web service description document. With the help of WordNet, a semantic analysis is conducted to reduce the dimension of the term vector and to make semantic expansion to meet the user’s service request. The process and algorithm of hierarchical clustering based semantic Web service discovery is discussed. Validation is carried out on the dataset.

Incorporating Semiotics into Fuzzy Logic to Enhance Clinical Decision Support Systems

In order to enhance the quality of care, healthcare organisations are increasingly resorting to clinical decision support systems (CDSSs), which provide physicians with appropriate health care decisions or recommendations. However, how to explicitly represent the diverse vague medical knowledge and effectively reason in the decision-making process are still problems we are confronted. In this paper, we incorporate semiotics into fuzzy logic to enhance CDSSs with the aim of providing both the abilities of describing medical domain concepts contextually and reasoning with vague knowledge. A semiotically inspired fuzzy CDSSs framework is presented, based on which the vague knowledge representation and reasoning process are demonstrated.

An Ontological Approach to Personalized Medical Knowledge Recommendation

Knowledge recommendation has become a promising method in supporting the clinicians’ decisions and improving the quality of medical services in the constantly changing clinical environment. However, current medical knowledge management systems cannot understand users’ requirements accurately and realize personalized recommendation. Therefore this chapter proposes an ontological approach based on semiotic principles to personalized medical knowledge recommendations. In particular, healthcare domain knowledge is conceptualized and an ontology-based user profile is built. Furthermore, the personalized recommendation mechanism is illustrated.