Zhang, Ji and Liu, Qing and Xu, Kai (2009) FlowRecommender: a workflow recommendation technique for process provenance. In: 8th Australasian Data Mining Conference (AusDM 2009): : Data Mining and Analytics , 1-4 Dec 2009, Melbourne, Australia.
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The increasingly complicated workflow systems necessitates the development of automated workflow recommendation techniques, which are able to not only speed up the workflow construction process, but also reduce the errors that are possibly made. The existing workflow recommendation systems are quite limited in that they cannot produce a correct recommendation of the next node if the upstream nodes/sub-paths that determine the occurrence of this node are not immediately connected with it. To solve this drawback, we propose in this paper a new workflow recommendation technique, called FlowRecommender. FlowRecommender features a more robust exploration capability to identify the upstream dependency patterns that are essential to the accuracy of workflow recommendation. These patterns are properly register offline to ensure a highly efficient online workflow recommendation. The experimental results confirm the promising effectiveness and efficiency of FlowRecommender.
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|Item Type:||Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)|
|Item Status:||Live Archive|
|Additional Information:||Published version deposited in accordance with the copyright policy of the publisher. Copyright c2009, Australian Computer Society, Inc. This paper appeared at the Eighth Australasian Data Mining Conference (AusDM 2009), Melbourne, Australia. Conferences in Research and Practice in Information Technology (CRPIT), Vol. 101, Paul J. Kennedy, Kok-Leong Ong and Peter Christen, Ed. Reproduction for academic, not-for profit purposes permitted provided this text is included.|
|Faculty / Department / School:||Historic - Faculty of Sciences - Department of Maths and Computing|
|Date Deposited:||20 Oct 2009 23:45|
|Last Modified:||31 Jul 2014 04:40|
|Uncontrolled Keywords:||FlowRecommender; automated workflow recommendation techniques|
|Fields of Research :||08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080109 Pattern Recognition and Data Mining|
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