PROCESSING EVENT INSTANCE DATA IN A CLIENT-SERVER ARCHITECTURE

• US 20130212158A1
• Filed: 03/30/2012
• Published: 08/15/2013
• Est. Priority Date: 02/15/2012
• Status: Abandoned Application

• Current Assignee: QPR Software Oyj
• Original Assignee: QPR Software Oyj
• Inventors: LEHTO, Teemu, HINKKA, Markku
• Application Number:
  US13/435,226
• Publication Number:
  US 20130212158A1
• Time in Patent Office: Days
• US Class Current: 709/203
• CPC Class Codes: G06Q 10/0631 Resource planning, allocation, distributing or scheduling for enterprises or organisations
• CPC Class Codes: G06Q 10/0633 Workflow analysis
• CPC Class Codes: G06Q 10/08 Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
• CPC Class Codes: H04L 67/01 Protocols
• CPC Class Codes: H04L 67/1008 based on parameters of servers, e.g. available memory or workload monitoring of computer activity G06F11/30

Abstract

A process analysis system (1-300) processes event data describing real-world processes (1-100). The process analysis system performs the following acts: importing event instance data sets from an information management system (1-200), each set comprising one or more attributes describing an event instance in the real-world process (1-100); for each event instance, determining a corresponding process instance based on at least the attributes; determining event order attribute(s) for each imported event instance data set based on other event instance data sets corresponding to the same process instance; forming an analysis result set based on at least the event instance data sets and at least one first or second attribute; the client(s) presenting an analysis utilizing the analysis result set.

Claims

1. A method for analyzing information derived from event data by a computer-implemented analysis system, which comprises a server and one or more clients, wherein the event data describes a real-world process the execution of which is supported by at least one information management system but the real-world process is not directly connectable with the computer-implemented analysis system, the method comprising the following acts performed by the server:

importing event instance data comprising a plurality of event instance data sets from the at least one information management system, wherein each event instance data set comprises one or more attributes describing an event instance in the real-world process;

determining for each imported event instance data set a corresponding process instance based on at least the attributes of the imported event instance data set;

determining at least one event order attribute for each imported event instance data set based on at least other event instance data sets corresponding to the same process instance;

creating a causal model based on at least the event instance data sets;

using the causal model to calculate a probability for at least one predicted future event for at least one process instance based on at least the causal model;

forming an analysis result set based on at least the event instance data sets and at least one predicted future event;

sending the analysis result set to one or more clients;

wherein the method further comprises;

at the one or more clients, presenting an analysis utilizing the analysis result set.

2. The method according to claim 1, wherein the server calculates the probability for an event of a particular event type.

3. The method according to claim 1, wherein the server calculates the probability for an event of a particular timestamp.

4. The method according to claim 1, wherein the server calculates the probability for a process instance to match any particular process variation.

5. The method according to claim 1, wherein the causal model is created based on at least linear correlations between event types derived from event instance data sets imported to the system.

6. The method according to claim 1, wherein the causal model is created based on at least separately imported general prediction data.

7. The method according to claim 1, wherein the server calculates the probability based on at least one additional event of a certain event type imported to the analysis system.

8. The method according to claim 7, further comprising:

the server suggesting an activity that maximizes a desired outcome based on the attributes of a set of process instances.

9. A computer-implemented analysis system comprising a server for supporting one or more clients, the server comprising:

at least one processing unit

memory for storing applications and data;

wherein the memory comprises program code instructions for instructing

the at least one processing unit to carry out the following steps;

importing event instance data comprising a plurality of event instance data sets from the at least one information management system, wherein each event instance data set comprises one or more attributes describing an event instance in the real-world process;

determining for each imported event instance data set a corresponding process instance based on at least the attributes of the imported event instance data set;

determining at least one event order attribute for each imported event instance data set based on at least other event instance data sets corresponding to the same process instance;

creating a causal model based on at least the event instance data sets;

using the causal model to calculate a probability for at least one predicted future event for at least one process instance based on at least the causal model;

forming an analysis result set based on at least the event instance data sets and at least one predicted future event;

sending the analysis result set to one or more clients.

10. The computer-implemented analysis system according to claim 9, wherein the server comprises multiple processing units and a load-balancing unit for distributing processing load among the multiple processing units.

11. A computer-readable memory comprising program code instructions for a server of a process analysis system that also comprises one or more clients, wherein the program code instructions, when executed by the server, cause the server to perform the steps of:

importing event instance data comprising a plurality of event instance data sets from the at least one information management system, wherein each event instance data set comprises one or more attributes describing an event instance in the real-world process;

determining for each imported event instance data set a corresponding process instance based on at least the attributes of the imported event instance data set;

determining at least one event order attribute for each imported event instance data set based on at least other event instance data sets corresponding to the same process instance;

creating a causal model based on at least the event instance data sets;

using the causal model to calculate a probability for at least one predicted future event for at least one process instance based on at least the causal model;

forming an analysis result set based on at least the event instance data sets and at least one predicted future event;

sending the analysis result set to one or more clients.