Title
Generating process model collection with diverse label and structural features
Abstract
The advancements in Business Process Management Systems (BPMS) have placed process models at the center of enterprise information systems. Due to the significant importance of process models, organizations are maintaining more and more process models to explicitly represent the flow of their business operations. The sheer number has led to the development of repositories to efficiently manage these collections. These repositories provide techniques for storing process models and searching relevant models against a given query process model. Searching involves comparing the query model with each source process model in the collection to compute the degree of similarity between query-source process model pair. While several techniques have been developed for that purpose, a direct comparison of these approaches have rarely been made. A key reason to that is, the absence of a freely available benchmark collection of process models that contains examples of process models with diverse features. To overcome that problem, we have employed a systematic and rigorous protocol to generate a diversified collection of process models, and compare it with the famous SAP's process model collection to establish the superiority of our collection. Further, we have applied a baseline approach to establish that the variants of process models (that we have generated) are significantly different from each other. It is pertinent to mention that our collection is freely available and we contend that the proposed collection will be useful in making a direct comparison of existing techniques and developing, evaluating and analyzing new techniques for process matching.
Year
DOI
Venue
2016
10.1109/INTECH.2016.7845083
2016 Sixth International Conference on Innovative Computing Technology (INTECH)
Keywords
Field
DocType
Information Systems,Information Retrieval,Process Modeling,Process Model Repositories,Benchmark Process Model Collection
Business process management,Data mining,Data collection,Business operations,Computer science,Process modeling,Enterprise information system,Business process modeling,Business process discovery,Benchmark (computing)
Journal
Volume
Issue
ISBN
8
2
978-1-5090-2001-0
Citations 
PageRank 
References 
1
0.36
17
Authors
4
Name
Order
Citations
PageRank
Khurram Shahzad116525.77
Kareem Shareef210.36
Rao Faizan Ali310.70
Muhammad Adeel42711.84