# US 2019/0012252 A1 · Systems and methods for automated analysis, screening, and reporting of group performance > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2019/0012252 A1 - Document ID: US20190012252A1 - Status: Published application - Kind: A1 - Application number: 16/128,379 - Filed: 2018-09-11 - Published: 2019-01-10 - Earliest claimed: 2013-08-01 - Assignees: Alpha Beta Analytics, LLC - Applicants: Alpha Beta Analytics, LLC - Inventors: Grigori KAPOUSTIN - Web page: https://patentgrep.com/patent/US20190012252A1 ## CPC - G06F 16/2455: Query execution - G06F 11/3006: {where the computing system is distributed, e.g. networked systems, clusters, multiprocessor systems (multiprogramming arrangements G06F9/46; allocation of resources G06F9/50)} - G06F 11/3452: {Performance evaluation by statistical analysis} - G06F 16/285: {Clustering or classification} - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) ## Abstract A method for quantifying performance of a group includes obtaining, for the group, historical group performance data, historical group factor exposure data for a plurality of predefined factors, and historical factor performance data for the plurality of predefined factors. The method includes generating historical group residual performance data for the group in accordance with the historical group performance data, the historical group factor exposure data for the plurality of predefined factors, and the historical factor performance data for the plurality of predefined factors. A respective entry in the historical group residual performance data represents member selection performance associated with the group. The method includes storing the historical group residual performance data for the group; and providing one or more values that represent the historical group residual performance data. ## Claims ### Claim 1 A computer system, comprising: one or more processors; and memory storing one or more programs for execution by the one or more processors, the one or more programs including instructions for: receiving, at the computer system, a request to quantify group residual performance associated with a first group; obtaining, at the computer system, historical group performance data for the first group; obtaining, at the computer system, historical group factor exposure data for a plurality of predefined factors for the first group; obtaining, at the computer system, historical factor performance data for the plurality of predefined factors for the first group; generating, at the computer system, historical group residual performance data for the first group in accordance with the historical group performance data for the first group, the historical group factor exposure data for the plurality of predefined factors for the first group, and the historical factor performance data for the plurality of predefined factors for the first group, wherein a respective entry in the historical group residual performance data represents member selection performance associated with the first group; storing, at the computer system, the historical group residual performance data for the first group; and providing one or more values that represent the historical group residual performance data. ### Claim 2 (depends on 1) The computer system of claim 1, wherein the first group includes a plurality of members, the plurality of members including at least one member of a first type and at least one member of a second type that is different from the first type. ### Claim 3 (depends on 1) The computer system of claim 1, wherein the first group includes a plurality of members, and all of the plurality of members in the first group are of a first type. ### Claim 4 (depends on 3) The computer system of claim 3, wherein: the first group is a respective group in a plurality of groups; the plurality of groups includes a second group that includes a plurality of members; and all of the plurality of members in the second group are of a second type that is different from the first type. ### Claim 5 (depends on 1) The computer system of claim 1, wherein: the first group is a respective group in a first set of groups, the first set of groups including a plurality of groups, and each respective group in the first set of groups including a plurality of members; and the one or more programs further include instructions for: for each respective group in the first set other than the first group: obtaining, at the computer system, historical group performance data for the respective group; obtaining, at the computer system, historical group factor exposure data for a plurality of predefined factors for the respective group; obtaining, at the computer system, historical factor performance data for the plurality of predefined factors for the respective group; and generating, at the computer system, respective historical group performance data for the respective group in accordance with the historical group performance data for the respective group, the historical group factor exposure data for the plurality of predefined factors for the respective group, and the historical factor performance data for the plurality of predefined factors for the respective group, wherein a respective entry in the respective historical group residual performance data for the respective group represents member selection performance associated with the respective group. ### Claim 6 (depends on 5) The computer system of claim 5, wherein the one or more programs further include instructions for: identifying a subset of groups in the first set based at least in part on the respective historical group residual performance data for each respective group in the first set; generating a second set of groups that consists of the subset of groups; and providing one or more values that represent the second set of groups. ### Claim 7 (depends on 6) The computer system of claim 6, wherein identifying the subset of groups in the first set is performed without regard to whether a respective group includes members of a particular type. ### Claim 8 (depends on 6) The computer system of claim 6, wherein all of the members in the first set of groups are of a first type. ### Claim 9 (depends on 6) The computer system of claim 6, wherein: a respective entry in the respective historical group residual performance data for a respective subset represents member selection performance associated with the respective subset during a respective time period in a predefined set of time periods; and identifying the subset of groups in a respective set includes identifying a predetermined number of groups having the highest respective entries in the respective historical group residual performance data during a particular time period in the predefined set of time periods. ### Claim 10 (depends on 9) The computer system of claim 9, wherein each respective time period in the predefined set of time periods spans one month. ### Claim 11 (depends on 6) The computer system of claim 6, wherein: a respective entry in the respective historical group residual performance data for a respective subset represents member selection performance associated with the respective subset during a respective time period in a predefined set of time periods; and identifying the subset of groups in a respective set includes identifying groups having respective entries in the respective historical group residual performance data that satisfy a predefined threshold during a particular time period in the predefined set of time periods. ### Claim 12 (depends on 6) The computer system of claim 6, wherein the one or more programs include instructions for: determining, for each respective group, a respective reliability value that indicates reliability of the respective historical group residual performance data of the respective subset over a predefined set of time periods; wherein identifying the subset of groups in a respective set includes identifying a predetermined number of groups having the highest respective reliability values. ### Claim 13 (depends on 12) The computer system of claim 12, wherein the one or more programs include instructions for: identifying a distribution of values associated with the reliability values; determining a first number of reliability values that are within a first range within the distribution of values; and determining whether the first number of reliability values exceeds a threshold number of reliability values by at least a predefined amount; wherein identifying the subset of groups in a respective set is further based on a determination that the first number of reliability values exceeds the threshold number of reliability values by at least the predefined amount. ### Claim 14 (depends on 6) The computer system of claim 6, wherein the one or more programs include instructions for: determining, for each respective group, a respective reliability value that indicates reliability of the respective historical group residual performance data of the respective subset over a predefined set of time periods; wherein identifying the subset of groups in a respective set includes identifying groups having respective reliability values that satisfy a predefined threshold. ### Claim 15 (depends on 6) The computer system of claim 6, wherein: the respective historical group residual performance data for a respective group includes: respective historical group residual performance data for the respective group over a first set of time periods; and respective historical group residual performance data for the respective group over one or more subsequent sets of time periods, wherein the one or more subsequent sets of time periods occur later in time than the first set of time periods; and the one or more programs include instructions for: determining, for each respective group, one or more respective autocorrelation values indicating a degree of autocorrelation between the respective historical group residual performance data for the respective group during the first set of time periods and the respective historical group residual performance data for the respective group during the one or more subsequent sets of time periods; wherein identifying the subset of groups in a respective set is further based at least in part on a determination that autocorrelation values for the subset of groups satisfy predefined autocorrelation criteria. ### Claim 16 (depends on 5) The computer system of claim 5, wherein: all of the members in the first set of groups are of a first type; a third set of groups includes a plurality of groups, each respective group in the third set of groups including a plurality of members; all of the members in the third set of groups are of a second type that is different from the first type; and the one or more programs further include instructions for: for each respective group in the third set: obtaining, at the computer system, historical group performance data for the respective group; obtaining, at the computer system, historical group factor exposure data for a plurality of predefined factors for the respective group; obtaining, at the computer system, historical factor performance data for the plurality of predefined factors for the respective group; and generating, at the computer system, respective historical group residual performance data for the respective group in accordance with the historical group performance data for the respective group, the historical group factor exposure data for the plurality of predefined factors for the respective group, and the historical factor performance data for the plurality of predefined factors for the respective group, wherein a respective entry in the historical group residual performance data for the respective group represents member selection performance associated with the respective group; identifying a subset of groups in the first set based at least in part on the respective historical group residual performance data for each respective group in the first set; identifying a subset of groups in the third set based at least in part on the respective historical group residual performance data for each respective group in the third set; generating a fourth set of groups that includes the identified subset of groups in the first set and the identified subset of groups in the third set; and providing one or more values that represent the fourth set of groups. ### Claim 17 (depends on 1) The computer system of claim 1, wherein the one or more programs further include instructions for: obtaining, for each member in the first group, historical use data for the respective member; and generating historical group member use data for the first group in accordance with the respective historical use timing data for each respective member in the first group; wherein: obtaining the historical group performance data for the first group includes: obtaining historical member performance data for the first group; and generating the historical group performance data for the first group in accordance with the historical group member use data for the first group and the historical member performance data for the first group; and obtaining the historical group factor exposure data for the plurality of predefined factors for the first group includes: obtaining historical member factor exposure data for the first group; and generating the historical group factor exposure data for the plurality of predefined factors for the first group in accordance with the historical group member use data for the first group and the historical member factor exposure data for the first group. ### Claim 18 (depends on 1) The computer system of claim 1, wherein obtaining the historical group factor exposure data for the plurality of predefined factors for the first group includes: obtaining initial historical group factor exposure data for the plurality of predefined factors for the first group; generating an aggregate historical group factor exposure value for the plurality of predefined factors for a group including all possible members, based on the initial historical group factor exposure data for the plurality of predefined factors for the first group; determining an offset between the aggregate historical group factor exposure value for the plurality of predefined factors for the group including all possible members and an expected aggregate historical group factor exposure value; and generating the historical group factor exposure data for the plurality of predefined factors for the first group based on the initial historical group factor exposure data for the plurality of predefined factors for the first group and the determined offset. ### Claim 19 (depends on 1) The computer system of claim 1, wherein: obtaining, at the computer system, the historical group performance data for the first group includes obtaining historical group performance data for at least a first subgroup in the first group and a second subgroup in the first group, wherein the first subgroup corresponds to a first time period, and wherein the second subgroup corresponds to a second time period distinct from the first time period. ### Claim 20 A method for quantifying performance of a group, comprising: receiving, at a computer system, a request to quantify group residual performance associated with a first group; obtaining, at the computer system, historical group performance data for the first group; obtaining, at the computer system, historical group factor exposure data for a plurality of predefined factors for the first group; obtaining, at the computer system, historical factor performance data for the plurality of predefined factors for the first group; generating, at the computer system, historical group residual performance data for the first group in accordance with the historical group performance data for the first group, the historical group factor exposure data for the plurality of predefined factors for the first group, and the historical factor performance data for the plurality of predefined factors for the first group, wherein a respective entry in the historical group residual performance data represents member selection performance associated with the first group; storing, at the computer system, the historical group residual performance data for the first group; and providing one or more values that represent the historical group residual performance data.