DOI:10.20894/IJDMTA.
Periodicity: Bi Annual.
Impact Factor:
SJIF:4.893 & GIF:0.787
Submission:Any Time
Publisher: IIR Groups
Language: English
Review Process:
Double Blinded

News and Updates

Author can submit their paper through online submission. Click here

Paper Submission -> Blind Peer Review Process -> Acceptance -> Publication.

On an average time is 3 to 5 days from submission to first decision of manuscripts.

Double blind review and Plagiarism report ensure the originality

IJDMTA provides online manuscript tracking system.

Every issue of Journal of IJDMTA is available online from volume 1 issue 1 to the latest published issue with month and year.

Paper Submission:
Any Time
Review process:
One to Two week
Journal Publication:
June / December

IJDMTA special issue invites the papers from the NATIONAL CONFERENCE, INTERNATIONAL CONFERENCE, SEMINAR conducted by colleges, university, etc. The Group of paper will accept with some concession and will publish in IJDMTA website. For complete procedure, contact us at admin@iirgroups.org

Paper Template
Copyright Form
Subscription Form
web counter
web counter
Published in:   Vol. 8 Issue 1 Date of Publication:   June 2019

APRM to Isolate Behavior (Frequent or Infrequent) by using Cross-Organizational Process Mining

Pavithra. J,Anette Regina. I

Page(s):   37-40 ISSN:   2278-2397
DOI:   10.20894/IJDMTA.102.008.001.007 Publisher:   Integrated Intelligent Research (IIR)

Process mining is a generally youthful and creating research zone with the primary thought of finding, checking and enhancing forms by removing data from occasion logs. Going out on a limb viewpoint on the business procedure administration (BPM) lifecycle has in this manner been perceived as a fundamental research stream. Notwithstanding significant information on hazard mindful BPM with an attention on process configuration, existing methodologies for real time chance observing regard occurrences as confined when identifying dangers. To address this hole, we propose an approach for Anomaly Predictive - Risk Monitoring (APRM). This approach naturally spreads chance data, which has been identified by means of hazard sensors, crosswise over comparable running occasions of a similar procedure progressively. We show APRMs capacity of prescient hazard checking by applying it with regards to a certifiable situation. With the expansion of distributed computing and shared foundations, occasion logs of various associations are accessible for examination where cross-hierarchical process mining remains with the open door for associations gaining from each other. Created proposal comes about demonstrate that the utilization of this approach can help clients to concentrate on the parts of process models with potential execution change, which are hard to spot physically and outwardly.