D 2015

A Versatile Algorithm for Predictive Graph Rule Mining

VACULÍK, Karel

Basic information

Original name

A Versatile Algorithm for Predictive Graph Rule Mining

Authors

VACULÍK, Karel (203 Czech Republic, guarantor, belonging to the institution)

Edition

1. vydání. Praha, Proceedings ITAT 2015: Information Technologies - Applications and Theory, p. 51-58, 8 pp. 2015

Publisher

CEUR-WS.org

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

Czech Republic

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

electronic version available online

RIV identification code

RIV/00216224:14330/15:00084898

Organization unit

Faculty of Informatics

ISBN

978-1-5151-2065-0

ISSN

Keywords (in Czech)

dolování z grafů; dolování z dat; dynamické grafy; dolování pravidel; časté vzory; predikce

Keywords in English

graph mining; data mining; dynamic graphs; rule mining; frequent patterns; prediction

Tags

International impact, Reviewed
Změněno: 28/4/2016 15:30, RNDr. Pavel Šmerk, Ph.D.

Abstract

V originále

Pattern mining in dynamic graphs has received a lot of attention in recent years. However, proposed methods are typically limited to specific classes of patterns expressing only a specific types of changes. In this paper, we propose a new algorithm, DGRMiner, which is able to mine patterns in the form of graph rules capturing various types of changes, i.e. addition and deletion of vertices and edges, and relabeling of vertices and edges. This algorithm works both with directed and undirected dynamic graphs with multiedges. It is designed both for the single-dynamic-graph and the set-of-dynamic-graphs scenarios. The performance of the algorithm has been evaluated by using two real-world and two synthetic datasets.