Abstract
People share various processes in daily lives on-line in natural language form (e.g., cooking recipes, “how-to guides” in eHow). We refer to them as personal process descriptions. Previously, we proposed Personal Process Description Graph (PPDG) to concretely represent the personal process descriptions as graphs, along with query processing techniques that conduct exact as well as similarity search over PPDGs. However, both techniques fail if no single personal process description satisfies all constraints of a query. In this paper, we propose a new approach based on our previous query techniques to query personal process descriptions by aggregation - composing fragments from different PPDGs to produce an answer. We formally define the PPDG Aggregated Search. A general framework is presented to perform aggregated searches over PPDGs. Comprehensive experiments demonstrate the efficiency and scalability of our techniques.
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- 1.
Business Process Model and Notation, www.bpmn.org.
- 2.
An anonymous node denotes an unnamed node in the query.
References
Awad, A.: BPMN-Q: a language to query business processes. In: The 2nd International Workshop on EMISA, pp. 115–128 (2007)
Awad, A., Sakr, S., Kunze, M., Weske, M.: Design by selection: a reuse-based approach for business process modeling. In: Jeusfeld, M., Delcambre, L., Ling, T.-W. (eds.) ER 2011. LNCS, vol. 6998, pp. 332–345. Springer, Heidelberg (2011)
Dijkman, R., Dumas, M., van Dongen, B.F., Käärik, R., Mendling, J.: Similarity of business process models: metrics and evaluation. Inf. Syst. 36(2), 498–516 (2011)
Hsu, J.O., Paik, H., Zhan, L.: Similarity search over personal process description graph. In: Wang, J., et al. (eds.) WISE 2015, Part I. LNCS, vol. 9418, pp. 522–538. Springer, Heidelberg (2015). doi:10.1007/978-3-319-26190-4_35
Hsu, J.O., Paik, H., Zhan, L., Ngu, A.H.H.: Aggregated search over personal process description graph. UNSW Computer Science and Engineering Technical report no. UNSW-CSE-TR-201608 (2016)
Kopliku, A., Pinel-Sauvagnat, K., Boughanem, M.: Aggregated search: a new information retrieval paradigm. ACM Comput. Surv. 46(3), 41:1–41:31 (2014)
Le, T.-H., Elghazel, H., Hacid, M.-S.: A relational-based approach for aggregated search in graph databases. In: Lee, S., Peng, Z., Zhou, X., Moon, Y.-S., Unland, R., Yoo, J. (eds.) DASFAA 2012, Part I. LNCS, vol. 7238, pp. 33–47. Springer, Heidelberg (2012)
Sakr, S., Awad, A.: A framework for querying graph-based business process models. In: WWW, pp. 1297–1300 (2010)
Sakr, S., Awad, A., Kunze, M.: Querying process models repositories by aggregated graph search. In: La Rosa, M., Soffer, P. (eds.) BPM Workshops 2012. LNBIP, vol. 132, pp. 573–585. Springer, Heidelberg (2013)
Wang, L.: CookRecipe: towards a versatile and fully-fledged recipe analysis and learning system. Ph.D. thesis, City University of Hong Kong (2008)
Xu, J., Paik, H., Ngu, A.H.H., Zhan, L.: Personal process description graph for describing and querying personal processes. In: Sharaf, M.A., Cheema, M.A., Qi, J. (eds.) ADC 2015. LNCS, vol. 9093, pp. 91–103. Springer, Heidelberg (2015)
Yan, X., Yu, P.S., Han, J.: Substructure similarity search in graph databases. In: SIGMOD, pp. 766–777 (2005)
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Hsu, J.O., Paik, Hy., Zhan, L., Ngu, A.H.H. (2016). Aggregated Search over Personal Process Description Graph. In: Hartmann, S., Ma, H. (eds) Database and Expert Systems Applications. DEXA 2016. Lecture Notes in Computer Science(), vol 9828. Springer, Cham. https://doi.org/10.1007/978-3-319-44406-2_19
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DOI: https://doi.org/10.1007/978-3-319-44406-2_19
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