Paper Info
Title
Querying business process models based on semantics
Abstract
In recent years, the technology of business process management is being more widely used, so that there are more and more business process models (graphs). How to manage such a large number of business process models is challenging, among which the business process model query is a basic function. For example, based on business process model query, the model designer can find the related models and evolve them instead of starting from scratch. It will save a lot of time and is less errorprone. To this end, we propose a language (BQL) for users to express their requirements based on semantics. For efficiency, we adopt an efficient method to compute the semantic features of business process models and use indexes to support the query processing. To make our approach more applicable, we consider the semantic similarity between labels. Our approach proposed in this paper is implemented in our system BeehiveZ. Analysis and experiments show that our approach works well.
Year
DOI
Venue
2011
10.1007/978-3-642-20152-3_13
DASFAA (2)
Keywords
Field
DocType
semantic similarity,related model,querying business process model,basic function,business process management,business process model,efficient method,semantic feature,business process model query,query processing,model designer,relational model,indexation
Artifact-centric business process model,Business process management,Data mining,Business process,Computer science,Business domain,Business process modeling,Business process discovery,Business Process Model and Notation,Database,Business rule
Conference
Volume
ISSN
Citations 
6588
0302-9743
20
PageRank 
References 
Authors
0.90
17
3
Name
Order
Citations
PageRank
Tao Jin1695.71
Jianmin Wang22446156.05
Lijie Wen345244.34