Recently, cross-department business processes are becoming more and more complex. Different kinds of coordination patterns exist among different departments, which make modeling and analysis work more difficult. To our best knowledge, there is no formal method to give systematic modeling and verification for the cross-department processes when considering different kinds of coordination patterns among different departments. This paper proposes such a method based on Petri nets. The WF-net model extended with resource and message factors, RM_WF_Net for short, is first introduced. Then, the formal model of tasks is proposed and its coordination relations are given. Next, RM_WF_Net modeling for intradepartment processes is investigated and cross-department coordination patterns, including message interaction pattern, resource interaction pattern, task collaboration pattern, procedure abstract, service outsourcing pattern, and process activation pattern, are formally defined. The soundness of the RM_WF_Net is verified based on the reachability graph. A running case of the crossdepartment medical diagnosis business process is given to validate our proposed method.

Process similarity measure plays an important role in business process management and is usually considered as a versatile solution to fulfill the effective utilization of process models. Although many studies have worked on different notions of process similarity, most of them are not precise enough, as they simply compare processes with respect to the model structure features or the model behavior features separately. To address the problem, in this paper, we propose to measure the business process similarity by considering both process models and process logs. The process models are pre-defined descriptions of business processes, and the process logs can be considered as an objective observation of the actual process execution behavior. The combination of both can help to better character business processes. More specifically, two effective frameworks together with four novel approaches are presented. The former first constructs a weighted business process graph (WBPG) from the process model and the process log, and then computes the similarity of two corresponding WBPGs by using the weighted graph edit distance measure and the weighted node adjacent relation similarity measure. The latter first measures the similarity of process logs and the similarity of process models separately, and then merges the results. Finally, by experimental evaluation, we demonstrate the effectiveness and the applicability of the proposed approaches by comparing them with the start of the art.

In the present work, the support vector machine (SVM) and Adaboost-SVM have been used to develop a classification model as a potential screening mechanism for a novel series of 5-HT1A selective ligands. Each compound is represented by calculated structural descriptors that encode topological features. The particle swarm optimization (PSO) and the stepwise multiple linear regression (Stepwise-MLR) methods have been used to search descriptor space and select the descriptors which are responsible for the inhibitory activity of these compounds. The model containing seven descriptors found by Adaboost-SVM, has showed better predictive capability than the other models. The total accuracy in prediction for the training and test set is 100.0% and 95.0% for PSO-Adaboost-SVM, 99.1% and 92.5% for PSO-SVM, 99.1% and 82.5% for Stepwise-MLR-Adaboost-SVM, 99.1% and 77.5% for Stepwise-MLR-SVM, respectively. The results indicate that Adaboost-SVM can be used as a useful modeling tool for QSAR studies.

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Existing business process similarity measure methods mainly focus on the control-flow (e.g., the activity and process model). However, the active factors of business processes, i.e., the roles that execute activities and organizations to which activities belong, have yet received enough attention. Roles are the subject of activities, many changes of process can be summarized as the management of roles and their relationship. In many cases, measuring process similarity from role perspective help find similarities and differences between processes and measure business process similarity more in a comprehensive way. This paper starts from activities and roles, and measures process similarity by constructing two role relation models. One is the Role Relation Network (RRN) that is defined based on the work delivery relation among roles, and the other is the Role Hierarchy Relation Network (RHRN) that is based on the role relation network and the role hierarchy graph. Then, we propose the corresponding business process similarity measure method. The proposed methods extend the applicability of existing process similarity measure methods to a larger application domain. Finally, experiments are designed to demonstrate the effectiveness of the proposed methods.