# US 10,121,115 B2 · Learning an entity's trust model and risk tolerance to calculate its risk-taking score > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,121,115 B2 - Document ID: US10121115B2 - Status: Granted - Kind: B2 - Application number: 15/630,299 - Filed: 2017-06-22 - Published: 2017-10-12 - Granted: 2018-11-06 - Earliest claimed: 2016-03-24 - Assignees: Www.Trustscience.Com Inc. - Applicants: www.TrustScience.com Inc. - Inventors: Evan Chrapko - Web page: https://patentgrep.com/patent/US10121115B2 ## CPC - G06Q 10/0635: Risk analysis of enterprise or organisation activities - G06N 7/01: Probabilistic graphical models, e.g. probabilistic networks - G06N 20/00: Machine learning - G06Q 10/42: Determination of affinities or common interests between users - G06Q 10/44: Identification of trends within social networks, e.g. identification of trending topics - G06Q 10/46: Determination of level of influence of users within social networking services - G06Q 10/48: using social graphs - G06Q 30/018: Certifying business or products - G06Q 40/03: Credit; Loans; Processing thereof - G06Q 40/08: Insurance - 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 - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS ## Abstract Systems and methods are described herein for learning an entity's trust model and risk tolerance. An entity's trust score may be calculated based on data from a variety of data sources, and this data may be combined according to a set of weights which reflect an entity's trust model and risk tolerance. For example, an entity may weight data of a certain type more heavily for certain types of transactions and another type of data more heavily for other transactions. By gathering data about the entity, a system may predict the entity's trust model and risk tolerance and adjust the set of weights accordingly for calculating trust scores. Furthermore, by monitoring how entities adjust weights for different transaction types, default weighting profiles may be created that are customized for specific transaction types. As another example, an entity's trust score, as reported to a requesting entity, may be adjusted based on that requesting entity's own trust model, or how “trusting” the requesting entity is. ## Claims ### Claim 1 A method, comprising: receiving, by a server device comprising a processor, a request from a client device for a trust score representative of a degree of trust between a requesting entity and a target entity, the request comprising requesting entity identification information identifying the requesting entity and target entity identification information identifying the target entity; determining, by the server device, the trust score based on the request, comprising: determining, by server the device, a baseline trust score for the target entity based on the target entity identification information; querying, by the server device, one or more network accessible data sources for defined trustworthiness information associated with the requesting entity based on the requesting entity identification information, wherein the defined trustworthiness information reflects a propensity for the requesting entity to trust other entities; determining, by the server device, an adjustment trust score for the requesting entity based on the defined trustworthiness information; and determining, by the server device, the trust score based on the baseline trust score for the target entity and the adjustment trust score; and providing, by the server device, the trust score to the client device based on the determining the trust score. ### Claim 2 (depends on 1) The method of claim 1, wherein the defined trustworthiness information comprises one or more keywords classified as trusting keywords and wherein the querying comprises performing, by the server device, a keyword search to identify the one or more keywords at the one or more network accessible data sources. ### Claim 3 (depends on 2) The method of claim 2, wherein the determining the adjustment trust score comprises determining the adjustment trust score based on the one or more keywords. ### Claim 4 (depends on 2) The method of claim 2, wherein the determining the adjustment trust score comprises determining the adjustment trust score based on a number of the one or more keywords identified. ### Claim 5 (depends on 1) The method of claim 1, wherein the determining the trust score comprises determining the trust score based on multiplication of the baseline trust score by the adjustment trust score. ### Claim 6 (depends on 1) The method of claim 1, wherein the defined trustworthiness information comprises personal information shared by the requesting entity, and wherein the determining the adjustment trust score further comprises determining the adjustment trust score based on an amount of the personal information shared by the requesting entity at the one or more network accessible data sources, and wherein the one or more network accessible data sources include social networking platforms. ### Claim 7 (depends on 1) The method of claim 1, wherein the defined trustworthiness information comprises personal information shared by the requesting entity, and wherein the determining the adjustment trust score further comprises determining the adjustment trust score based on a frequency at which the requesting entity shares the personal information at the one or more network accessible data sources, and wherein the one or more network accessible data sources include social networking platforms. ### Claim 8 (depends on 1) The method of claim 1, further comprising: receiving, by the server device, activity information that indicates an activity to be performed between the requesting entity and the target entity; and determining, by the server device, the adjustment trust score based on historical activity information that reflects a level of trust exhibited by the trusting entity in association with past performance of the activity or a similar activity. ### Claim 9 (depends on 8) The method of claim 8, further comprising: determining, by the server device, a recommendation regarding whether the requesting entity should perform the activity with the target entity based on the trust score; and providing, by the server device, the recommendation to the client device in association with the trust score. ### Claim 10 (depends on 1) The method of claim 1, wherein the determining the adjustment trust score comprises determining the adjustment trust score based on rating information associated with the requesting entity that reflects how trusting the requesting entity is for the other entities as determined by one or more entities other than the requesting entity. ### Claim 11 (depends on 1) The method of claim 1, wherein the baseline trust score associated with the target entity is based on social graph data that indicates a level of social connectivity between the requesting entity and the target entity. ### Claim 12 A server device, comprising: a processor; and a memory that stores executable instructions that, when executed by the processor, facilitate performance of operations, comprising: receiving, via a network, a request from a client device for a trust score representative of a degree of trust between a requesting entity and a target entity, the request comprising requesting entity identification information identifying the requesting entity and target entity identification information identifying the target entity; determining the trust score based on the request, comprising: determining a baseline trust score for the target entity based on the target entity identification information; querying one or more network accessible data sources for defined trustworthiness information associated with the requesting entity based on the requesting entity identification information, wherein the defined trustworthiness information reflects a propensity for the requesting entity to trust other entities; determining an adjustment trust score for the requesting entity based on the defined trustworthiness information; and determining the trust score based on the baseline trust score for the target entity and the adjustment trust score; and providing the trust score to the client device via the network based on the determining the trust score. ### Claim 13 (depends on 12) The device of claim 12, wherein the defined trustworthiness information comprises one or more keywords classified as trusting keywords and wherein the querying comprises performing a keyword search to identify the one or more keywords at one or more network accessible data sources. ### Claim 14 (depends on 13) The device of claim 13, wherein the determining the adjustment score comprises determining the adjustment score based on the one or more keywords. ### Claim 15 (depends on 12) The device of claim 12, wherein the defined trustworthiness information comprises personal information shared by the requesting entity and wherein the determining the adjustment score comprises determining the adjustment score based on an amount of the personal information shared by the requesting entity at the one or more network accessible data sources. ### Claim 16 (depends on 12) The device of claim 12, wherein the operations further comprise: receiving activity information that indicates an activity to be performed between the requesting entity and the target entity; and determining the adjustment trust score based on historical activity information that reflects a level of trust exhibited by the trusting entity in association with past performance of the activity or a similar activity. ### Claim 17 (depends on 12) The device of claim 12, wherein the determining the adjustment trust score comprises determining the adjustment trust score based on rating information associated with the requesting entity that reflects how trusting the requesting entity is for the other entities as determined by one or more entities other than the requesting entity. ### Claim 18 A non-transitory machine-readable storage medium, comprising executable instructions that, when executed by a processor, facilitate performance of operations, comprising: receiving a request for a trust score representative of a degree of trust between a requesting entity and a target entity, the request comprising requesting entity identification information identifying the requesting entity and target entity identification information identifying the target entity; determining the trust score based on the request, comprising: determining a baseline trust score for the target entity based on the target entity identification information; querying one or more network accessible data sources for defined trustworthiness information associated with the requesting entity based on the requesting entity identification information, wherein the defined trustworthiness information reflects a propensity for the requesting entity to trust other entities; determining an adjustment trust score for the requesting entity based on the defined trustworthiness information; and determining the trust score based on a baseline trust score for the target entity and the adjustment trust score; and providing a representation of the trust score to the requesting entity in response to the determining the trust score. ### Claim 19 (depends on 18) The non-transitory machine-readable storage medium of claim 18, the operations further comprising: receiving activity information that indicates an activity to be performed between the requesting entity and the target entity; and determining the adjustment trust score based on historical activity information that reflects a level of trust exhibited by the trusting entity in association with past performance of the activity or a similar activity. ### Claim 20 (depends on 19) The non-transitory machine-readable storage medium of claim 19, the operations further comprising: determining a recommendation regarding whether the requesting entity should perform the activity with the target entity based on the trust score; and providing the recommendation to the requesting entity in association with the trust score.