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Representing and Visualizing Mined Artful Processes in MailOfMine

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  1. Representing and Visualizing Mined Artful Processes inMailOfMine Claudio Di Ciccio, Massimo Mecella, TizianaCatarci HCI-KDD @ USAB 2011: Information Quality in e-HealthGraz, 2011, November the 24th

  2. Motivation (1) Artful processes and knowledge workers • Artful processes [HillEtAl06] • informal processes typically carried out by those people whose work is mental rather than physical (managers, professors, researchers, engineers, etc.) • “knowledge workers”[ACTIVE09] • Knowledge workers create artful processes “on the fly” • Though artful processes are frequently repeated, they are not exactly reproducible, even by their originators, nor can they be easily shared. Representing and Visualizing Mined Artful Processes in MailOfMine Claudio Di Ciccio (DIS, SAPIENZA – Università di Roma)

  3. Motivation (2) E-mail conversations • In collaborative contexts, knowledge workers share their information and outcomes with other knowledge workers • E.g., a software development mgr. • Typically, by means of several e-mail conversations • E-mail conversations are actual traces of running processes that knowledge workers adhere to Representing and Visualizing Mined Artful Processes in MailOfMine Claudio Di Ciccio (DIS, SAPIENZA – Università di Roma)

  4. Motivation (3) Processes from e-mail conversations • From the collection of e-mail messages, you can extract the processes that lay behind • Related e-mail conversations are traces of their runs • Valuable advantages for users • Automated discovery of formal representations • with no effort for knowledge workers • Tidy organization for naïve best practices kept only in mind • Opportunity to share and compare the knowledge on methodologies • Automated discovery of bottlenecks, delays, structural defects • from the analysis of previous runs • E-mail conversations are a kind of semi-structured text • this approach is not tailored to the electronic mail • it can be extended to the analysis of other semi-structured texts Representing and Visualizing Mined Artful Processes in MailOfMine Claudio Di Ciccio (DIS, SAPIENZA – Università di Roma)

  5. Motivation (4) Some areas of applicability • Personal information management (PIM) • how to organize one’s own activities, contacts, etc. through the usage of software [CatarciEtAl07, ACTIVE09] • Information warfare • in supporting anti-crime intelligence agencies • Enterprise engineering • for knowledge-heavy industries, where preserving documents making up product data is not enough[SmVortex, Heutelbeck11] • eHealth • for the automatic discovery of medical treatment procedures on top of patient health records Representing and Visualizing Mined Artful Processes in MailOfMine Claudio Di Ciccio (DIS, SAPIENZA – Università di Roma)

  6. The approach How to represent and infer artful processes • Representation • Declarative workflows [vanDerAalstEtAl09] for representing artful processes • Regular grammars to express declarative workflows constraints • Mining • Object Matching [ZardettoEtAl10] for • clustering e-mail conversations • finding the matching between activity and tasks instances • Regular expression mining [GarofalakisEtAl99] for inferring constraints • Supervised learning to group activities into processes • Text mining information extraction to determine tasks out of e-mail messages [CohenEtAl04, SakuraiEtAl05] Representing and Visualizing Mined Artful Processes in MailOfMine Claudio Di Ciccio (DIS, SAPIENZA – Università di Roma)

  7. Algorithm (1) From the e-mail archive to key parts Mail archive Mail Database Conversations KeyParts Multi-format mail storage plug-in based crawlers [ZardettoEtAl10]-based clustering algorithm [CarvalhoEtAl04] -based filter Representing and Visualizing Mined Artful Processes in MailOfMine Claudio Di Ciccio (DIS, SAPIENZA – Università di Roma)

  8. Key Parts Concatenation Algorithm (2) Activityindicium [ZardettoEtAl10]-based [CohenEtAl04,SakuraiEtAl05] -based task extractor From key parts to the activities Tasks [GarofalakisEtAl99] -basedpattern miner Activities Representing and Visualizing Mined Artful Processes in MailOfMine Claudio Di Ciccio (DIS, SAPIENZA – Università di Roma)

  9. Algorithm (3) From activities to the processes Supervised learning Process indicium [GarofalakisEtAl99] -basedpattern miner Process Representing and Visualizing Mined Artful Processes in MailOfMine Claudio Di Ciccio (DIS, SAPIENZA – Università di Roma)

  10. On the visualization of processes The imperative model • Represents the whole process at once • The most used notation is based on a subclass of Petri Nets (namely, the Workflow Nets) Representing and Visualizing Mined Artful Processes in MailOfMine Claudio Di Ciccio (DIS, SAPIENZA – Università di Roma)

  11. On the visualization of processes If A is performed, B must be perfomed, no matter before or afterwards (responded existence) The declarative model • Rather thanusing a procedural language for expressing the allowed sequence of activities, it is based on the description of workflows through the usage of constraints • the idea is that every task can be performed, except the ones which do not respect such constraints Whenever B is performed, C must be performed afterwards and B can not be repeated until C is done (alternate response) The notation here is based on [VanDerAalstEtAl06] (DecSerFlow) Representing and Visualizing Mined Artful Processes in MailOfMine Claudio Di Ciccio (DIS, SAPIENZA – Università di Roma)

  12. On the visualization of processes Imperative vS declarative Declarative Declarative models work better in presence of a partial specification of the process scheme Imperative Representing and Visualizing Mined Artful Processes in MailOfMine Claudio Di Ciccio (DIS, SAPIENZA – Università di Roma)

  13. Representation of artful processes Tasks Existence constraints An example of expected outcome • Notation based on [VanDerAalstEtAl06] (DecSerFlow) Relation constraints Representing and Visualizing Mined Artful Processes in MailOfMine Claudio Di Ciccio (DIS, SAPIENZA – Università di Roma)

  14. On the visualization of processes An example of DecSerFlow [VanDerAalstEtAl06] notation • You might want to run a legal trace like this: • 〈a3, a3, a3, a2, a2, a3, a4, a5, a6, a7, a6, a5 〉 • What we want to state here is that such a notation is probably not quite intuitive You could even start from here No, it is not the initial action Representing and Visualizing Mined Artful Processes in MailOfMine Claudio Di Ciccio (DIS, SAPIENZA – Università di Roma)

  15. On the visualization of processes Our proposal • We do not consider a static graph-based global representation alone the best suitable solution. • A graphical representation, easy to understand at a first glimpse, must be used. • Idea: • when presenting the process schema (static view): • a local view on tasks/activities, showing related constraints only; • a global view on the process, either: • basic (less information, less symbols), or • extended (more information, more symbols, extending (a)); • (2) can work as a kind of navigation map for (1) • when presenting the running instance (dynamic view): • a dynamic interactive trace representation diagram, based on the local static view notation. Representing and Visualizing Mined Artful Processes in MailOfMine Claudio Di Ciccio (DIS, SAPIENZA – Università di Roma)

  16. On the visualization of processes Introducing the new local view: the rationale Representing and Visualizing Mined Artful Processes in MailOfMine Claudio Di Ciccio (DIS, SAPIENZA – Università di Roma)

  17. On the visualization of constraints The static local view: some examples Representing and Visualizing Mined Artful Processes in MailOfMine Claudio Di Ciccio (DIS, SAPIENZA – Università di Roma)

  18. On the representation of processes The static global view Basic Extended Representing and Visualizing Mined Artful Processes in MailOfMine Claudio Di Ciccio (DIS, SAPIENZA – Università di Roma)

  19. A GUI sketch Local and global views together Representing and Visualizing Mined Artful Processes in MailOfMine Claudio Di Ciccio (DIS, SAPIENZA – Università di Roma)

  20. On the representation of constraints Dynamic view Representing and Visualizing Mined Artful Processes in MailOfMine Claudio Di Ciccio (DIS, SAPIENZA – Università di Roma)

  21. References Cited articles and resources, in order of appearance • [BranderEtAl11] Brander, S., Hinkelmann, K., Hu, B., Martin, A., Riss, U. V., Thönssen, B., Witschel, H. F.. Refining process models through the analysis of informal work practice. In BPM, Lecture Notes in Computer Science (6896), 116–131. Springer (2011). • [HillEtAl06] Hill, C., Yates, R., Jones, C., Kogan, S.L.: Beyond predictable workflows: Enhancing productivity in artful business processes. IBM Systems Journal 45(4), 663–682 (2006) • [ACTIVE09] Warren, P., Kings, N., et al.: Improving knowledge worker productivity - the active integrated approach. BT Technology Journal 26(2), 165–176 (2009) • [CatarciEtAl07] Catarci, T., Dix, A., Katifori, A., Lepouras, G., Poggi, A.: Task-centred information management. Proc. DELOS Conference, LNCS 4877 (2007) • [SmVortex] Smart vortex – management and analysis of massive data streams to support large-scale collaborative engineering projects. FP7 IP Project: http://www.smartvortex.eu/ • [Heutelbeck11] Heutelbeck, D.: Preservation of enterprise engineering processes by social collaboration software (2011), personal communication, to appear in Proc. COLLIN2011 - 2nd Symposium on Collective Intelligence • [vanDerAalstEtAl09] van der Aalst, W.M.P., Pesic, M., Schonenberg, H.: Declarative workflows: Balancing between flexibility and support. Computer Science - R&D 23(2), 99–113 (2009) • [ZardettoEtAl10] Zardetto, D., Scannapieco, M., Catarci, T.: Effective automated object matching. Proc. ICDE 2010 • [CohenEtAl04] Cohen, W.W., Carvalho, V.R., Mitchell, T.M.: Learning to classify email into “speech acts”. Proc. EMNLP 2004 • [SakuraiEtAl05] Sakurai, S., Suyama, A.: An e-mail analysis method based on text mining techniques. Appl. Soft Comput. 6(1), 62–71 (2005) • [CarvalhoEtAl04] Carvalho, V.R., Cohen, W.W.: Learning to extract signature and reply lines from email. Proc. CEAS 2004 • [GarofalakisEtAl99] Garofalakis, M.N., Rastogi, R., Shim, K.: Spirit: Sequential pattern mining with regular expression constraints. Proc. VLDB 1999 • [vanDerAalstEtAl06] van der Aalst, W.M.P., Pesic, M.: Decserflow: Towards a truly declarative service flow language. Proc. WS-FM 2006 • [Pnueli77] Pnueli, A.: The Temporal Logic of Programs. Proc. 18th Annual Symposium on Foundations of Software Technology and Theoretical Computer Science, 1977 Representing and Visualizing Mined Artful Processes in MailOfMine Claudio Di Ciccio (DIS, SAPIENZA – Università di Roma)