1. Automated Correlation Discovery for Semi-Structured Business Processes DEBS 2011 Szabolcs Rozsnyai, Aleksander Slominski, Geetika T. Lakshmanan

6. Big Picture and Context

12. Statistics Calculation 1/2

14. Example Example

15. Example - Index The attribute cardinality (i.e. Index) contains a map of each value and how often each of those values occurred . Example

16. Example - Card 4 Unique Values Determines the number of different values for the attribute. Example

17. Example - Cnt Cnt=5 For certain attributes the number might be smaller as they can be null or missing Cnt=5 For certain attributes the number might be smaller as they can be null or missing Cnt=5 For certain attributes the number might be smaller as they can be null or missing Represents the total number of instances in which the attribute occurs . As the data structure does not work on a defined schema it is possible that the attribute does not occur in every instance. Represents the total number of instances in which the attribute occurs . As the data structure does not work on a defined schema it is possible that the attribute does not occur in every instance. Example

18. Example - AvgAttributeLength AvgAttributeLength is calculated Represents the average attribute length of the current attribute. This is an indicator about the potential uniqueness of a value. A long value might be the sign that attribute might be a unique identifier. Unique identifiers such as OrderId is a potential attribute that occurs in other types and thus forms a correlation. This may also be misleading since a textual description may be very long and is in fact unique but it is never used for correlating artefacts. Example

19. Example - InferencedType Determines DataType Defines the type of an attribute . The type of an attribute is an important characteristic for correlation discovery to reduce the problem space of correlation candidates. The chances that a type would correlate with another attribute given that the type contains mostly alpha-numeric attributes are very low. The determination of the type is made with a fault tolerance of 0.9 (e.g. min. 90% of the values must be numeric), and we refer to this as a parameter Phi. Example

20. Example – The rest of the types… Example

21. Example – The rest of the types… Example

26. Example – Determining Mappables The Mappable Attribute can be seen as means to reduced search space of potentially correlating attributes of a type. One approach is to set an upper threshold of how often a value of an attribute can occur. The assumption is that if it occurs more then x times it is unlikely that it is a correlation candidate. x… Cardinality of a value i… Attribute of a type { xi | x < Gamma } Card < Gamma where Gamma = 10 For instance in this domain it might be unlikely that a shipment has more than 10 orders. However this might cause problems in other domains or for certain relationships (one customer has definitely more than 10 orders). Example

29. Example – DifferenceSet for all Permutations Example OrderReceived.OrderId = ShipmentCreated.ShipmentId OrderReceived.OrderId = ShipmentCreated.OrderId OrderReceived.OrderId = TransportStarted.TransportId OrderReceived.OrderId = TransportStarted.ShipmentId … A/B = {x | x  A  x  B} |A/B| <= DiffTreshold 100% 0% 100% 100% … DiffTreshold = 0.95 OrderReceived.OrderId = ShipmentCreated.OrderId ShipmentCreated.ShipmentId = TransportStarted.ShipmentId ShipmentCreated.ShipmentId = TransportEnded.ShipmentId TransportStarted.TransportId = TransportEnded.TransportId TransportEnded.TransportId = TransportStarted.TransportId Resulting candidates of Correlation Pairs with 100% overlapping SetDiff SetDiff 0% 0% 0% 0% 0%

32. Example – AvgAttributeLength Example OrderReceived.OrderId = ShipmentCreated.OrderId ShipmentCreated.ShipmentId = TransportStarted.ShipmentId ShipmentCreated.ShipmentId = TransportEnded.ShipmentId TransportStarted.TransportId = TransportEnded.TransportId TransportEnded.TransportId = TransportStarted.TransportId SetDiff 0% 0% 0% 0% 0% AvgAttrLength 0 0 0 0 0

34. Example – LevenshteinDistance Example OrderReceived.OrderId = ShipmentCreated.OrderId ShipmentCreated.ShipmentId = TransportStarted.ShipmentId ShipmentCreated.ShipmentId = TransportEnded.ShipmentId TransportStarted.TransportId = TransportEnded.TransportId TransportEnded.TransportId = TransportStarted.TransportId SetDiff 0% 0% 0% 0% 0% AvgAttrLength 0 0 0 0 0 LevenshteinDistance 0 0 0 0 0

35. Example – Weight Calculation Example OrderReceived.OrderId = ShipmentCreated.OrderId ShipmentCreated.ShipmentId = TransportStarted.ShipmentId ShipmentCreated.ShipmentId = TransportEnded.ShipmentId TransportStarted.TransportId = TransportEnded.TransportId TransportEnded.TransportId = TransportStarted.TransportId SetDiff 0% 0% 0% 0% 0% Avg Attribute Length 0 0 0 0 0 Levenshtein Distance 0 0 0 0 0 SetDiff AvgAttrLenght LevenshteinDistance 60% 20% 20% Confidence 100% 100% 100% 100% 100% Weight is adjustable!

37. Correlation Discovery

38. Correlation Discovery Refinement

41. THANK YOU! Questions?