Corporate fraud these days represents a huge cost to our economy. In the paper we address one specific type of corporate fraud, internal transaction fraud. Given the omnipresence of stored history logs, the field of process mining rises as an adequate answer to mitigating internal transaction fraud. Process mining diagnoses processes by mining event logs. This way we can expose opportunities to...

Curricular analytics is the area of learning that looks for insights and evidence on relationship between curricular elements degree achievement outcomes. For higher education institutions, can be useful identifying strengths weaknesses curricula justifying changes in pathways students. This work presents study trajectories as processes (i.e., sequence events) using process mining techniques. S...

Mining of frequent itemsets is a fundamental data mining task. Past research has proposed many efficient algorithms for the purpose. Recent work also highlighted the importance of using constraints to focus the mining process to mine only those relevant itemsets. In practice, data mining is often an interactive and iterative process. The user typically changes constraints and runs the mining al...

Recently, the Task Force on Process Mining released the Process Mining Manifesto. The manifesto is supported by 53 organizations and 77 process mining experts contributed to it. The active contributions from end-users, tool vendors, consultants, analysts, and researchers illustrate the growing relevance of process mining as a bridge between data mining and business process modeling. This paper ...

Process mining is a family of methods to analyze event logs produced during the execution of business processes in order to extract insights regarding their performance and conformance with respect to normative or expected behavior. The landscape of process mining methods and use cases has expanded considerably in the past decade. However, the field has evolved in a rather ad hoc manner without...

A problem addressed by an information mining project is transforming existing business information of an organization into useful knowledge for decision making. Thus, the traditional software development process for requirements elicitation cannot be used to acquire required information for information mining process. In this context, a process of requirements gathering for information mining p...

customers are the most valuable asset of an organization. due to high contest in the business field, it is necessary to regard the customer relationship management (crm) of the enterprise. data mining and machine learning methods been utilized by businesses in recent years in order to improve crm. crm is the strategy for building, managing, and strengthening loyal and long lasting customer rela...