The cluster hypothesis revisited
SIGIR '85 Proceedings of the 8th annual international ACM SIGIR conference on Research and development in information retrieval
A language modeling approach to information retrieval
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
A vector space model for automatic indexing
Communications of the ACM
A study of smoothing methods for language models applied to Ad Hoc information retrieval
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Sap R/3 Process Oriented Implementation
Sap R/3 Process Oriented Implementation
The Journal of Machine Learning Research
Cluster-based retrieval using language models
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
A case-based reasoning framework for workflow model management
Data & Knowledge Engineering - Special issue: Advances in business process management
Two-scale image retrieval with significant meta-information feedback
Proceedings of the 13th annual ACM international conference on Multimedia
User performance versus precision measures for simple search tasks
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
LDA-based document models for ad-hoc retrieval
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Measuring similarity between semantic business process models
APCCM '07 Proceedings of the fourth Asia-Pacific conference on Comceptual modelling - Volume 67
Similarity search for web services
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Measuring Similarity between Business Process Models
CAiSE '08 Proceedings of the 20th international conference on Advanced Information Systems Engineering
Graph Matching Algorithms for Business Process Model Similarity Search
BPM '09 Proceedings of the 7th International Conference on Business Process Management
Ranking BPEL Processes for Service Discovery
IEEE Transactions on Services Computing
Fast business process similarity search with feature-based similarity estimation
OTM'10 Proceedings of the 2010 international conference on On the move to meaningful internet systems - Volume Part I
FNet: an index for advanced business process querying
BPM'12 Proceedings of the 10th international conference on Business Process Management
Investigating clinical care pathways correlated with outcomes
BPM'13 Proceedings of the 11th international conference on Business Process Management
Textual and Content-Based Search in Repositories of Web Application Models
ACM Transactions on the Web (TWEB)
Querying business process model repositories
World Wide Web
Hi-index | 0.00 |
Large organizations tend to have hundreds of business processes. Discovering and understanding similarities among business processes can be useful to organizations for a number of reasons including better overall process management and maintenance. In this paper we present a novel and efficient approach to cluster and retrieve business processes. A given set of business processes are clustered based on their underlying topic, structure and semantic similarities. In addition, given a query business process, top k most similar processes are retrieved based on clustering results. In this work, we bring together two not wellconnected schools of work: statistical language modeling and structure matching and combine them in a novel way. Our approach takes into account both high-level topic information that can be collected from process description documents and keywords as well as detailed structural features such as process control flows in finding similarities among business processes. This ability to work with processes that may not always have formal control flows is particularly useful in dealing with real-world business processes which are not always described formally. We developed a system to implement our approach and evaluated it on several collections of industry best practice processes and real-world business processes at a large IT service company that are described at varied levels of formalisms. Our experimental results reveal that the combined language modeling and structure matching based retrieval outperforms structure-matching-only techniques in both mean average precision and running time measures.