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This paper provides a formalized definition of the application problem of compound condition query (CCQ) and a formal method of applying requirements elicitation based on trace information space derived from trace algebra. With the formalized process of solving the application problem of CCQ, formal requirements specification of application of CCQ is given, a formalized and automatic mapping of the results of requirements elicitation to the formal requirements specification is performed, the software system model and the application code are developed. Through a sample application of comprehensive query on housing information, the feasibility of formalized and automatic software development for the application problem of CCQ is proved. The result has important implications for the other problems regarding formalization and automatic software development.

Link prediction is an important content in the related fields of social networks. Nowadays, the link prediction algorithm based on node similarity is the research hotspot. Node similarity is usually calculated by common neighbours, however, the impact of each common neighbour on the link is different, and how to distinguish the different roles of common neighbours needs to be further studied. The paper proposes the concept of node link strength and redefines the calculation method of node similarity. The new algorithm takes into account the link strength between the common neighbour nodes and the predicted nodes, better to reflect the effect of each common neighbour node. The algorithm is carried out experiments on five real social network datasets, the prediction results show that the algorithm's prediction accuracy is more effective than the existing mainstream algorithms based on node similarity and maintains low time complexity.

As the online social network become increasingly popular nowadays, performing viral marketing over it has become the focus of many marketing management. How to select a fixed number of initial users from the total population with the purpose of maximizing the profits has long been open as a typical discrete approximation problem. However most of the existing solutions under the setting of online social network tried to traverse every node using network properties which is time-consuming and ineffective. This paper attacks the problem successfully by implementing intelligent algorithms such as GA, DE, PSO. Considering of the huge search space, we sharply decrease the scalability of the network through analyzing the datasets and sampling the data according to a power law property. Experiment results showed that the model we designed for solving viral marketing problem outperform other current search methods.

This paper presents a novel trust mechanism and web services, and introduces the application of Web Services, and designs for submarine power distribution system model, and discusses the core that the implement of the model controls and business processes.

Model transformation is one of the core operations in model driven architecture (MDA) and engineering (MDE), which happens among heterogeneous models in various modeling languages. Constructing rules for such model transformation is time consuming and of great challenge. A question arises that how to describe these knowledge in standardized form and reuse them to construct model transformation rules quickly and in low cost. In this paper, transformation pattern is introduced and well defined according to the design pattern in software development. It represents transformation rules in a modeling language independent form and is easy to reuse. This study proposes a model transformation framework based on pattern and a rule constructing method. Seven reusable atomic patterns are given and nine rule extracting strategies based on this are figured. Finally, this study presents an algorithm which incorporates these strategies for constructing transformation rules. Case study in transformation between two business process models in BPMN and JPDL shows the applicability of the method in real model transformation.

Internetware is endowed with more flexibility in the dynamic, open network. However, it is facing a big challenge in trust evaluation on interaction between two components. This paper proposes an effective way of trust evaluation based on the punishment mechanism and proved its function to resist malicious attack. As trust relationships can be obtained by the recommendations of other Internetwares, thus a virtual trust information network naturally formed. In this way, the trust relationship of an Internetware can be derived without direct interaction. However, the problem lies in we might get malicious information and be led to misjudgment in such a complex and changeable network. Therefore, we put forward an algorithm based on the idea of RIP routing algorithm. The algorithm is proved to be efficient and reliable through experiment.

Ontology is an explicit specification of a conceptualization on semantic and knowledge. This paper presents a formal definition on ontology and gives an example. Then, a method to measuring semantic similarity is presented. Semantic similarity is divided into concept similarity and description similarity. A calculation of semantic similarity between concepts in ontology is presented by the hierarchy of ontology concepts. To make the calculation of semantic similarity between concepts more similar to human's subjective judgment, semantic similarity is divided into concept similarity and description similarity; the final semantic similarity is produced by merging concept similarity and description similarity. Finally, the optimized parameter settings are gained through the experiment results.

A method based on Petri net is presented for analyzing active database rules. Cyclic rule set, inconsistent rule set and contradictory rule set can be detected automatically by using Petri nets. These rule sets can be corrected or rearranged properly by the user in order to guarantee the system's termination, consistency and correctness.