Margarita Knyazeva

A graph-based data mining approach to preventing financial fraud: a case study

In this paper, we present a graph-based approach to a data mining problem of exploring and revealing domain groups of users prone to committing financial fraud. Data mining in financial applications refers to extracting and organizing knowledge from large amount of legal and financial data according to certain criteria. In order to solve this problem, information about the companies should be well-defined and arranged according to a data mining process model. Here, we introduced a graph-based model to formalize large amounts of data as well as a methodology of graph centers of interest to solve classification and prediction data mining tasks that are vital to handle fraud detection. A graph-based model consists of a set of real objects, such as shareholders, vendors, and directors, with some object attributes and relations between the objects. IBM i2 software is used to visualize data and graph model representation.

Searching Method of Fuzzy Internally Stable Set as Fuzzy Temporal Graph Invariant

In this paper we consider the problem of finding the invariant of a fuzzy temporal graph, namely, a fuzzy internally stable set. Fuzzy temporal graph is a generalization of a fuzzy graph on the one hand, and a temporal graph on the other hand. In this paper, a temporal fuzzy graph is considered, in which the connectivity degree of vertices varies in discrete time. The notion of maximum internally stable subset of fuzzy temporal graph is considered. A method and an algorithm for finding all maximal internally stable sets are proposed which makes it possible to find a fuzzy internally stable set. The example of definition of internal stable fuzzy set is considered as well.

A fuzzy graph multi-mode approach to modelling and solving scheduling problem with limited resources

This paper reports on a graph-based approach to modelling and solving combinatorial resource-constrained scheduling problem with respect to possibility to perform the individual activities in alternative ways (modes). These modes vary depending on processing time, time lags to other activities and resource requirements. A fuzzy scheduling problem can be formally defined by a number of activities-nodes that should be scheduled to minimize the project duration subject to generalized precedence relations, may require some units of limited in time use resources. Solution methodology is based on branch and bound procedure to operate with resource requirements and precedence constraints as well as selection of one single activity mode to construct a schedule.

Scheduling Alternatives with Respect to Fuzzy and Preference Modeling on Time Parameters

This paper is devoted to modelling and solving resource-constrained fuzzy scheduling problem. We study flexibilities in scheduling that reflect level of preference or attitude of decision-maker towards imprecise concepts, relations between them and fuzzy variables. Special combinations of alternatives or modes allow to take into account these flexibilities and construct exact branch-and-bound scheduling procedure.

Allocation Method for Fuzzy Interval Graph Centers Based on Strong Connectivity

In this paper the problem of defining service centres optimum allocation in transportation network is observed. It is supposed that transportation network is described by a fuzzy interval graph. The notion of fuzzy set of strong connectivity is introduced. It is shown that the problem of service centers location can be reduced to a problem of finding fuzzy set of strong connectivity. The method and algorithm of finding fuzzy set of strong connectivity is considered in this paper. The example of finding optimum allocation of centers in fuzzy interval graph is considered.

Optimal Allocation Centers in Second Kind Fuzzy Graphs with the Greatest Base Degree

The problem of optimal allocation of service centers is considered in this paper. It is supposed that the information received from GIS is presented like second kind fuzzy graphs. Method of optimal location as method of finding fuzzy base set of second kind fuzzy graph is suggested. Basis of this method is building procedure of reachability matrix of second kind fuzzy graph in terms of reachability matrix of first kind fuzzy graph. This method allows solving not only problem of finding of optimal service centers location but also finding of optimal location k-centers with the greatest degree and selecting of service center numbers. The algorithm of the definition of fuzzy base set for second kind fuzzy graphs is considered. The example of finding optimum allocation centers in second kind fuzzy graph is considered too.

An Attributed Graph Mining Approach to Detect Transfer Pricing Fraud

This paper presents an attributed graph-based approach to an intricate data mining problem of revealing affiliated, interdependent entities that might be at risk of being tempted into fraudulent transfer pricing. We formalize the notions of controlled transactions and interdependent parties in terms of graph theory. We investigate the use of clustering and rule induction techniques to identify candidate groups (hot spots) of suspect entities. Further, we find entities that require special attention with respect to transfer pricing audits using network analysis and visualization techniques in IBM i2 Analysts Notebook.