# US 2018/0322397 A1 · Detecting case families with anomalous frequencies in rule-based decision policies > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2018/0322397 A1 - Document ID: US20180322397A1 - Status: Published application - Kind: A1 - Application number: 15/588,912 - Filed: 2017-05-08 - Published: 2018-11-08 - Earliest claimed: 2017-05-08 - Assignees: International Business Machines Corporation - Applicants: International Business Machines Corporation - Inventors: Ulrich M. Junker; Thierry Kormann - Web page: https://patentgrep.com/patent/US20180322397A1 ## CPC - G06N 5/025: Extracting rules from data - G06Q 10/103: {Workflow collaboration or project management} - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS - G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR ## Abstract Disclosed embodiments provide techniques for analyzing rule-based decision policies. Data is obtained for a plurality of events. The events can be customer behaviors, or other events that can be interpreted by rules. A rule set is obtained for the plurality of events, where the rule set comprises a plurality of rules. Regions are computed based on the rules within the rule set. Frequency data is computed for the plurality of events, and an indication of frequency density is provided for each region. This allows a user to quickly and easily analyze the effectiveness and appropriateness of the rules as they relate to observed customer behaviors. Recommendations for rule changes can be provided as an output of the disclosed techniques. ## Claims ### Claim 1 A computer-implemented method for analyzing rule-based decision policies comprising: obtaining data for a plurality of events; obtaining a rule set for the plurality of events, wherein the rule set comprises a plurality of rules embodied in a computer-based business management system, wherein the computer-based business management system includes a processor; computing frequency data with the processor for the plurality of events based on the rule set; and computing regions based on the rules within the rule set, wherein each region corresponds to a subset of the plurality of events; providing a recommendation of one or more rule modifications based on the frequency data; and rendering the recommendation on a computer display. ### Claim 2 (depends on 1) The method of claim 1, further comprising: determining a frequency density range for the plurality of events based on the frequency data; and wherein computing regions based on the rules within the rule set is based on the frequency density range. ### Claim 3 (depends on 1) The method of claim 1, wherein computing the region comprises computing a rectangle. ### Claim 4 (depends on 1) The method of claim 1, further comprising identifying candidates for rule consolidation. ### Claim 5 (depends on 1) The method of claim 1, further comprising identifying candidates for rule separation. ### Claim 6 (depends on 1) The method of claim 1, further comprising identifying a region in a specified density range. ### Claim 7 (depends on 1) The method of claim 1, further comprising identifying a region of a uniform frequency density. ### Claim 8 An electronic computing device for analyzing rule-based decision policies, comprising: a processor; a memory coupled to the processor, the memory containing instructions, that when executed by the processor, perform the steps of: obtaining data for a plurality of events; obtaining a rule set for the plurality of events, wherein the rule set comprises a plurality of rules; computing frequency data for the plurality of events based on the rule set; determining a frequency density range for the plurality of events based on the frequency data; computing regions based on the rules within the rule set, wherein each region corresponds to a subset of the plurality of events; providing a recommendation of one or more rule modifications based on the frequency data; and rendering the recommendation on a computer display. ### Claim 9 (depends on 8) The electronic computing device of claim 8, wherein the memory further contains instructions, that when executed by the processor, performs the step of computing the region by computing a polygon. ### Claim 10 (depends on 8) The electronic computing device of claim 8, wherein the memory further contains instructions, that when executed by the processor, performs the step of computing the region by computing a rectangle. ### Claim 11 (depends on 8) The electronic computing device of claim 8, wherein the memory further contains instructions, that when executed by the processor, performs the step of identifying candidates for rule consolidation. ### Claim 12 (depends on 8) The electronic computing device of claim 8, wherein the memory further contains instructions, that when executed by the processor, performs the step of identifying candidates for rule separation. ### Claim 13 (depends on 8) The electronic computing device of claim 8, wherein the memory further contains instructions, that when executed by the processor, performs the step of comprising identifying a region in a specified density range. ### Claim 14 (depends on 8) The electronic computing device of claim 8, wherein the memory further contains instructions, that when executed by the processor, performs the step of identifying a region of a uniform frequency density. ### Claim 15 A computer program product for analyzing rule-based decision policies on an electronic computing device, the electronic computing device comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the electronic computing device to: obtain data for a plurality of events; obtain a rule set for the plurality of events, wherein the rule set comprises a plurality of rules; compute frequency data for the plurality of events based on the rule set; determine a frequency density range for the plurality of events based on the frequency data; compute regions based on the rules within the rule set, wherein each region corresponds to a subset of the plurality of events; provide a recommendation of one or more rule modifications based on the frequency data; and render the recommendation on a computer display. ### Claim 16 (depends on 15) The computer program product of claim 15, further comprising program instructions executable by the processor to cause the electronic computing device to compute a polygon region. ### Claim 17 (depends on 15) The computer program product of claim 15, further comprising program instructions executable by the processor to cause the electronic computing device to compute a rectangle region. ### Claim 18 (depends on 15) The computer program product of claim 15, further comprising program instructions executable by the processor to cause the electronic computing device to identify candidates for rule consolidation. ### Claim 19 (depends on 15) The computer program product of claim 15, further comprising program instructions executable by the processor to cause the electronic computing device to identify candidates for rule separation. ### Claim 20 (depends on 15) The computer program product of claim 15, further comprising program instructions executable by the processor to cause the electronic computing device to identify a region of a uniform frequency density.