CFP last date
20 June 2024
Reseach Article

Stock Crime Detection using Graph Mining

by Jigyasha Arora, Pawan Kumar Mishra, Prakash Joshi
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 90 - Number 10
Year of Publication: 2014
Authors: Jigyasha Arora, Pawan Kumar Mishra, Prakash Joshi

Jigyasha Arora, Pawan Kumar Mishra, Prakash Joshi . Stock Crime Detection using Graph Mining. International Journal of Computer Applications. 90, 10 ( March 2014), 4-9. DOI=10.5120/15754-4317

@article{ 10.5120/15754-4317,
author = { Jigyasha Arora, Pawan Kumar Mishra, Prakash Joshi },
title = { Stock Crime Detection using Graph Mining },
journal = { International Journal of Computer Applications },
issue_date = { March 2014 },
volume = { 90 },
number = { 10 },
month = { March },
year = { 2014 },
issn = { 0975-8887 },
pages = { 4-9 },
numpages = {9},
url = { },
doi = { 10.5120/15754-4317 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-06T22:10:39.351524+05:30
%A Jigyasha Arora
%A Pawan Kumar Mishra
%A Prakash Joshi
%T Stock Crime Detection using Graph Mining
%J International Journal of Computer Applications
%@ 0975-8887
%V 90
%N 10
%P 4-9
%D 2014
%I Foundation of Computer Science (FCS), NY, USA

Previously existing graph mining algorithm typically assumes that database is relatively static. To overcome that we proposed a new algorithm which deals with large database including the features which captures the properties of graph in few parameters and check the relationship among them in both left as well as right direction, thus adopting DFS as well as BFS approach. It further finds the sub graph by traversing the graph and extracting the desired pattern. The proposed algorithm is used for detection of crime in stock market by capturing the properties and identifying the relationship & associations that may exist between the person involved in that crime which prevent several crimes that might occur in future. We have used the ECLIPSE for the implementation of proposed algorithm and Neo4j is the graph database used for analysis.

  1. Kamrul Abedin Tarafder, Shah Mostafa Khaled, moham Ashraful Islam," Reverse Apriori algorithm for frequent pattern mining , Medwell journals, 2008.
  2. Usama Fayyad, Gregory Piatetsky-Shapiro, and Padhraic Smyth," From Data Mining to Knowledge Discover Databases", AI MagazineVolume 17 Number 3 (1996) (© AAAI)
  3. Justin J. Miller,"Graph Database Applications and Concept with Neo4j",Proceedings of the Southern Association for Information System Conference, Atlanta, GA, USA March 23rd- 24th, 2013
  4. Ingrid Fischer and Thorsten Meinl,"Graph Based Molecular Data Mining - An Overview",?0-7803-8566-7/04/$20. 00 c. 2004 IEEE
  5. Xifeng Yan and Jiawei Han,"gSpan: Graph-BasedSubstructure"http://oldwww. comlab. ox. ac. uk/oucl/groups/machlearn/PTE
  6. Deepayan Chakrabarti, Yiping Zhan and Christos Faloutsos,"R- MAT: A Recursive Model for Graph Mining", ‡ School of Computer Science, CMU.
  7. Frank Eichinger,Klemens B¨ohm and Matthias Huber, Improved Software Fault Detection with Graph Mining", Appearing in the 6th International Workshop on Mining and Learning with Graphs, Helsinki, Finland, 2008.
  8. JunmeiWang, WynneHsu Mong and Li Lee Chang Sheng," "A Partition-Based Approach to Graph Mining", Proceedings of the 22nd International Conference on Data Engineering (ICDE'06)8-7695-2570-9/06 $20. 00 © 2006 IEEE
  9. Garima Jaiswal and Arun Prakash Agrawal"Comparativeanalysis of Relational and Graph databases", IOSR Journal of Engineering (IOSRJEN).
  10. Ciro Cattuto, André Panisson, Marco Quaggiotto and Alex Averbuch,"Time-varying Social Networks in a GraphDatabase"http://www. sociopatterns. org
  11. Quist-Aphetsi Kester,"Criminal Geographical Profiling: Using FCA for Visualization and Analysis of Crime Data",Email: kquist-aphetsi@gtuc. edu. gh / kquist@ieee. org
  12. G. Kishore Kumar, Dr. V. K. Jayaraman " Clustering of Complex Networks and Community Detection Using Group Search Optimization".
  13. Hsinchun Chen, WingyanChung, Jennifer Jie Xu, Gang Wang Yi Qin and Michael Chau," Crime Data Mining: AGeneral Framework and Some Examples", 0018-9162/04/$20. 00 © 2004 IEEE
  14. Tibor Bosse, Charlotte Gerritsen, and Jan Treur," Analysis of Criminal Behaviour ".
  15. Sytske Besemer," The impact of timing and frequency of parental criminal behaviour and risk factors on offspring offending", an Institute of Criminology University of Cambridge, Cambridge, UK Version of record first published: 05 Nov 2012.
Index Terms

Computer Science
Information Sciences


Graph database Graph mining DFSS Sub graph.