Chungang Yan

A Novel Method for Calculating Service Reputation

Owing to their rapid development, services are increasing rapidly in quantity. The consequence is that there are so many services that share the same or similar functions. Therefore, it is important to select a credible and optimal service. Reputation as one of the important parameters of services plays a significant role in the decision support for service selection. This paper proposes a novel two-phase method to calculate service reputation. The first phase uses a dynamic weight formula to calculate reputation such that it can reflect the latest tendency of a service. The second one uses an olfactory response formula to mitigate the negative effect of unfair ratings. Some experiments are conducted and the results validate the effectiveness of the proposed method.

Modeling and Validating E-Commerce Business Process Based on Petri Nets

E-commerce and online shopping with a third-party payment platform have rapidly developed recently, and encountered many fault tolerance and security problems concerned by users. The causes of these problems include malicious behavior and imperfect business processes. The latter lead to the emergence of security vulnerabilities and loss of user funds which become more and more serious these years. We focus on the business process of e-commerce, and propose a formal model for constructing an e-commerce business process called an E-commerce Business Process Net. It integrates both data and control flows based on Petri nets. Rationality and transaction consistency are defined and validated to guarantee the transaction properties of an e-commerce business process. This paper offers a complete methodology for modeling and validating an e-commerce system with a third-party payment platform from the view point of a business process. Its use enables a designer to identify errors early in the design process and correct them before the deployment phase. In order to demonstrate the applicability and feasibility of the methodology, we have modeled and validated a real-world e-commerce business process and discovered the problems that cause the violation of transaction properties.

A Relational Taxonomy of Services for Large Scale Service Repositories

With the rapid development of service-oriented computing (SOC) and service-oriented architecture (SOA), the number of services is rapidly increasing. How to organize and manage services effectively in repositories to improve the efficiency of service discovery and composition is important. This paper proposes three categorization rules to classify services for a large scale repository to form a relational taxonomy. The service retrieve scope can be drastically narrowed by this taxonomy. Therefore, the efficiency of service discovery and service composition can be greatly improved. We evaluate and compare the performance of the proposed method and other related ones via a publicly available test set, ICEBE05. The experimental results validate the effectiveness and high efficiency of the proposed one.

An Indexing Network Model for Information Services and Its Applications

Along with the enormous amount of information service resources on the Internet, it is increasingly necessary to consider the urgent problems it has brought, such as diversity, heterogeneity, disorder, and redundancy. Existing service technologies like P2P, grid computing, Web service, and cloud computing, mainly focus on a certain type of service resources, and they do not provide a basic model that can organize and manage various types of service resources existing on the current Internet. Therefore, to achieve better organization and management of service resources, thereby providing more valuable information services for Internet users, this paper introduces an indexing network model and five related normal forms to advance the field. As a basic model, indexing network organizes and manages various information service resources through analyzing the relationships among them. On this basis, applying the model to web page resources, we show two case studies. They are implemented using cloud distributed systems (Hadoop + Habse + Zookeeper) built on Sugon-Tongji cloud platform located at Tongji University. 70 million web pages are crawled and two indexing networks are constructed. Through analysis of service applications provided by them, we show the advantages of the proposed indexing network model to organize web pages and keywords, which can provide and support more knowledgeable and valuable search related services, thereby better meeting the complex and diverse needs of Internet users.

Analyzing E-Commerce Business Process Nets via Incidence Matrix and Reduction

E-commerce business process nets (EBPNs) are a novel formal model for describing and validating e-commerce systems including interactive parties such as shopper, merchant, and third-party payment platform. Data errors and nondeterminacy of the data states during the trading process can be depicted with the help of EBPNs. However, the problem about how to analyze EBPNs remains largely open. To analyze their data-liveness, data-boundedness, and reachability, this paper presents two analysis methods. For EBPNs, reachability analysis is proposed based on a 3-D incidence matrix method. Additionally, reduction methods are proposed for a special EBPN. Finally, the validity and reliability of the proposed methods are illustrated via the examples of e-commerce systems.

An event timeline extraction method based on news corpus

Event extraction is an important research point in information extraction area, and news event extraction has a greater practical significance. The existing methods of extracting news event, which starts from the time element, is to identify the date sentences hold by Natural Language Processing and extract the event on the date by Text Clustering. However, they only process the news that holds a time-tag and gives up the news that has no accurate date, which easily leads an extraction deviation of significant events and reduces the accuracy of ordering the significant events. In this paper, improvement for this defect is to calculate the similarities between sentences to put part of the non-time-tag sentences into the right date container, thereby the accuracy of ordering the significant event is improved. Through experiments and compared with the existing methods, the accuracy of ordering the significant events in this paper is improved by 14.6%.

Detecting Data Inconsistency Based on the Unfolding Technique of Petri Nets

The errors of data inconsistency occur in a concurrent system when some concurrent operations are conducted improperly. The model-checking technique is widely used to detect them based on the state transition graph. However, the state space explosion problem is the biggest obstacle for this technique, since the state transition graph is based on the interleaving semantics that can result in a rapid increase of the graph scale. In addition, data inconsistency is closely related with concurrent operations, but the state transition graph hardly characterizes concurrency due to its interleaving semantics. The unfolding technique of Petri nets can both alleviate the state explosion and characterize concurrency because it is based on the concurrent semantics. In this paper, we define Petri net with data to model concurrent systems with three kinds of data operations: read , write, and delete, and then formalize data inconsistency. We propose an unfolding method to produce a finite complete prefix (FCP) for each PD-net. Then, a matrix that represents all concurrency relations of transitions is constructed in view of FCP. Furthermore, the error of data inconsistency can be detected via this matrix. The related algorithms and the developed tool are introduced, and experiments illustrate their effectiveness and advantages. An example of industrial information system shows the usefulness of our study.

A continuous identity verification method based on free-text keystroke dynamics

Currently, existing continuous identity verification methods mostly need to analyze a lot of keystroke data to ensure the authentication credibility. To achieve certification results with less data, in the paper, a new continuous verification method is proposed. This method, based on free-text keystroke dynamics, excavates the nearest character sequences of the users from their typing patterns, then builds Gaussian model based on the users nearest character sequences, and at last grades the attempts to verify identity of the users based on Gaussian probability density function. Experimental results demonstrate that efficacy of the proposed method with accuracy of 90.5%, which achieve a false-alarm-rate of 5.3% under thirty characters. In the field of continuous identity verification, our method can be applied to reduce the verification cycle and ensure the reliability of the verification.

Checking the Inconsistent Data in Concurrent Systems by Petri Nets with Data Operations

The general Petri nets are not suitable to model the data operations of concurrent read and coverable write. Therefore, Petri net with data operations (PN-DO) is defined, which extends contextual nets with write arcs and some other components. Its execution semantics are defined, and a newmethod is proposed to construct its reachability graph that is of a smaller scale than traditional reachability graph. Based on this kind of reachability graph, we propose a method to check the errors of inconsistent data and missing data. Meanwhile, case studies are given to illustrate the effectiveness of our methods.

Detecting data-flow errors based on Petri nets with data operations

In order to guarantee the correctness of business processes, not only control-flow errors but also data-flow errors should be considered. The control-flow errors mainly focus on deadlock, livelock, soundness, and so on. However, there are not too many methods for detecting data-flow errors. This paper defines Petri nets with data operations U+0028 PN-DO U+0029 that can model the operations on data such as read, write and delete. Based on PN-DO, we define some data-flow errors in this paper. We construct a reachability graph with data operations for each PN-DO, and then propose a method to reduce the reachability graph. Based on the reduced reachability graph, data-flow errors can be detected rapidly. A case study is given to illustrate the effectiveness of our methods.