System and method for detecting interaction and influence in networks

• US 10,735,532 B2
• Filed: 10/20/2016
• Issued: 08/04/2020
• Est. Priority Date: 10/20/2015
• Status: Active Grant

• Current Assignee: Axon Vibe AG
• Original Assignee: Axon Vibe AG
• Inventors: Oberli, Roman, Annicq, Thomas
• Primary Examiner(s): Kindred, Alford W
• Assistant Examiner(s): Htay, Lin Lin M
• Application Number:
  US15/298,353
• Publication Number:
  US 20170111462A1
• Time in Patent Office: 1,384 Days
• CPC Class Codes: G06F 16/2379 Updates performed during online database operations; commit processing
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/288 Entity relationship models
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: H04L 67/52 specially adapted for the location of the user terminal
• CPC Class Codes: H04L 67/535 Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34

Abstract

Systems and methods for providing location-based recommendation to a user that leverages common characteristics between the user and other users in a network such that the common characteristics are derived based on monitoring and analyzing user information at different times and locations. A computing device receives information associated with each of a plurality of entities in a network, including a transaction and an activity, the transaction and the activity each being associated with a location and a time. The computing device receives updated information and creates a data structure relating the first entity and a subset of the plurality of entities based on the updated information. The computing device determines a recommendation related to the updated information, calculates a relevance value between entities in the subset of entities, and transmits the recommendation to one of the entities.

Claims

1. A computerized method for providing a location-based recommendation to a user that leverages common characteristics between the user and other users in a network such that the common characteristics are derived based on monitoring and analyzing user information at different times and locations, the computerized method comprising:

receiving, by a computing device, information associated with each of a plurality of entities in a network, the information including at least one of a transaction or an activity, the at least one of the transaction or the activity each being associated with a location and a time;

receiving, by the computing device, at least one of;

updated location information associated with a first entity of the plurality of entities,

updated transaction information associated with the first entity, or

updated activity information associated with the first entity;

determining, by the computing device, based on the at least one of the updated location information, the updated transaction information, or the updated activity information, that the first entity is on a travel excursion;

creating, by the computing device, a data structure relating the first entity and a subset of the plurality of entities, the subset being chosen based on the each of the entities in the subset having information related to the travel excursion, the data structure including a node representing each of the entities in the subset and links connecting the nodes;

determining, by the computing device, a recommendation of at least one of a transaction and an activity based on the information related to the at least one of the updated location information, the updated transaction information, or the updated activity information;

determining, by the computing device, based on the at least one of the updated location information, the updated transaction information, or the updated activity information, that the travel excursion is to a new location;

calculating, by the computing device, a relevance value for each of the links connecting the first entity with other entities having information associated with the recommendation, the relevance value being based on the determination that the travel excursion is to the new location; and

transmitting, by the computing device, the recommendation to at least one of the first entity or a second entity in the subset when at least one relevance value exceeds a threshold,

thereby providing the recommendation to an entity based on information that is common to the entity and other entities in the network and derived based on monitoring and analyzing entity information at different times and locations.

2. The computerized method of claim 1, further comprising:

receiving, by the computing device, a relevance indication from the at least one of the first entity or the second entity relating to the recommendation; and

updating, by the computing device, at least one of the relevance value or the threshold based on the relevance indication.

3. The computerized method of claim 1, wherein calculating the relevance value comprises:

calculating, by the computing device, a relationship score between at least one of the first entity or the second entity and other entities in the network, the relationship score being based on a combination of a duration metric, a vintage metric, an interaction metric, a trust and variety metric, a control metric, and a harmony metric;

calculating, by the computing device, a centrality score for each of the entities in the subset, the centrality score being based on a combination of a degree metric, a closeness metric, and a betweenness metric; and

combining, by the computing device, the relationship score and the centrality score to form the relevance value.

4. The computerized method of claim 3, wherein:

the duration metric is associated with a duration of a relationship between the at least one of the first entity or the second entity and other entities in the network;

the vintage metric is associated with a time of a prior interaction between the at least one of the first entity or the second entity and other entities in the network;

the interaction metric is associated with a number of times a connection was established in a time period between the at least one of the first entity or the second entity and other entities in the network;

the trust and variety metric is associated with a number of different types of communications being used by the at least one of the first entity or the second entity and other entities in the network;

the control metric is associated with a hierarchy between the at least one of the first entity or the second entity and other entities in the network;

the harmony metric is associated with a synchronicity of an interaction between the at least one of the first entity or the second entity and other entities in the network;

the degree metric is associated with a number of links associated with each node corresponding to the at least one of the first entity or the second entity and other entities in the network;

the closeness metric is associated with a path length between a node corresponding to the at least one of the first entity or the second entity and nodes corresponding to other entities in the network; and

the betweenness metric is associated with a path length between each pair of nodes.

5. The computerized method of claim 1, wherein the updated location information comprises the first entity being co-located with another entity of the plurality of entities.

6. The computerized method of claim 1, wherein the updated location information comprises a location being visited by the first entity for a first time.

7. A non-transitory computer readable medium having executable instructions operable to cause an apparatus to:

receive information associated with each of a plurality of entities in a network, the information including at least one of a transaction or an activity, the at least one of the transaction or the activity each being associated with a location and a time;

receive at least one of;

updated location information associated with a first entity of the plurality of entities,

updated transaction information associated with the first entity, or

updated activity information associated with the first entity;

determine, based on the at least one of the updated location information, the updated transaction information, or the updated activity information, that the first entity is on a travel excursion;

create a data structure relating the first entity and a subset of the plurality of entities, the subset being chosen based on the each of the entities in the subset having information related to the travel excursion, the data structure including a node representing each of the entities in the subset and links connecting the nodes;

determine a recommendation of at least one of a transaction or an activity based on the information related to the at least one of the updated location information, the updated transaction information, or the updated activity information;

determine, based on the at least one of the updated location information, the updated transaction information, or the updated activity information, that the travel excursion is to a new location;

calculate a relevance value for each of the links connecting the first entity with other entities having information associated with the recommendation, the relevance value being based on the determination that the travel excursion is to the new location; and

transmit the recommendation to at least one of the first entity or a second entity in the subset when at least one relevance value exceeds a threshold,

thereby providing the recommendation to an entity based on information that is common to the entity and other entities in the network and derived based on monitoring and analyzing entity information at different times and locations.

8. The non-transitory computer readable medium of claim 7, wherein the apparatus is further caused to:

receive a relevance indication from the at least one of the first entity or the second entity relating to the recommendation; and

update at least one of the relevance value or the threshold based on the relevance indication.

9. The non-transitory computer readable medium of claim 7, wherein to calculate the relevance value, the apparatus is further caused to:

calculate a relationship score between at least one of the first entity or the second entity and other entities in the network, the relationship score being based on a combination of a duration metric, a vintage metric, an interaction metric, a trust and variety metric, a control metric, and a harmony metric;

calculate a centrality score for each of the entities in the subset, the centrality score being based on a combination of a degree metric, a closeness metric, and a betweenness metric; and

combine the relationship score and the centrality score to form the relevance value.

10. The non-transitory computer readable medium of claim 9, wherein:

the duration metric is associated with a duration of a relationship between the at least one of the first entity or the second entity and other entities in the network;

the vintage metric is associated with a time of a prior interaction between the at least one of the first entity or the second entity and other entities in the network;

the interaction metric is associated with a number of times a connection was established in a time period between the at least one of the first entity or the second entity and other entities in the network;

the trust and variety metric is associated with a number of different types of communications being used by the at least one of the first entity or the second entity and other entities in the network;

the control metric is associated with a hierarchy between the at least one of the first entity or the second entity and other entities in the network;

the harmony metric is associated with a synchronicity of an interaction between the at least one of the first entity or the second entity and other entities in the network;

the degree metric is associated with a number of links associated with each node corresponding to the at least one of the first entity or the second entity and other entities in the network;

the closeness metric is associated with a path length between a node corresponding to the at least one of the first entity or the second entity and nodes corresponding to other entities in the network; and

the betweenness metric is associated with a path length between each pair of nodes.

11. The non-transitory computer readable medium of claim 7, wherein the updated location information comprises the first entity being co-located with another entity of the plurality of entities.

12. The non-transitory computer readable medium of claim 7, wherein the updated location information comprises a location being visited by the first entity for a first time.

13. A computing device for providing a location-based recommendation to a user that leverages common characteristics between the user and other users in a network such that the common characteristics are derived based on monitoring and analyzing user information at different times and locations, the computing device comprising:

data storage; and

a processor in communication with the data storage, and configured to run a module stored in memory that is configured to cause the processor to;

receive information associated with each of a plurality of entities in a network, the information including at least one of a transaction or an activity, the at least one of the transaction or the activity each being associated with a location and a time;

receive at least one of;

updated location information associated with a first entity of the plurality of entities,

updated transaction information associated with the first entity, or

updated activity information associated with the first entity;

determine, based on the at least one of the updated location information, the updated transaction information, or the updated activity information, that the first entity is on a travel excursion;

create a data structure relating the first entity and a subset of the plurality of entities, the subset being chosen based on the each of the entities in the subset having information related to the travel excursion, the data structure including a node representing each of the entities in the subset and links connecting the nodes;

determine a recommendation of at least one of a transaction or an activity based on the information related to the at least one of the updated location information, the updated transaction information or the updated activity information;

determine, based on the at least one of the updated location information, the updated transaction information, or the updated activity information, that the travel excursion is to a new location;

calculate a relevance value for each of the links connecting the first entity with other entities having information associated with the recommendation, the relevance value being based on the determination that the travel excursion is to the new location; and

transmit the recommendation to at least one of the first entity or a second entity in the subset when at least one relevance value exceeds a threshold,

thereby providing the recommendation to an entity based on information that is common to the entity and other entities in the network and derived based on monitoring and analyzing entity information at different times and locations.

14. The computing device of claim 13, wherein the processor is further caused to:

receive a relevance indication from the at least one of the first entity or the second entity relating to the recommendation; and

update at least one of the relevance value or the threshold based on the relevance indication.

15. The computing device of claim 13, wherein to calculate the relevance value, the processor is further caused to:

calculate a relationship score between at least one of the first entity or the second entity and other entities in the network, the relationship score being based on a combination of a duration metric, a vintage metric, an interaction metric, a trust and variety metric, a control metric, and a harmony metric;

calculate a centrality score for each of the entities in the subset, the centrality score being based on a combination of a degree metric, a closeness metric, and a betweenness metric; and

combine the relationship score and the centrality score to form the relevance value.

16. The computing device of claim 15, wherein:

the duration metric is associated with a duration of a relationship between the at least one of the first entity or the second entity and other entities in the network;

the vintage metric is associated with a time of a prior interaction between the at least one of the first entity or the second entity and other entities in the network;

the interaction metric is associated with a number of times a connection was established in a time period between the at least one of the first entity or the second entity and other entities in the network;

the trust and variety metric is associated with a number of different types of communications being used by the at least one of the first entity or the second entity and other entities in the network;

the control metric is associated with a hierarchy between the at least one of the first entity or the second entity and other entities in the network;

the harmony metric is associated with a synchronicity of an interaction between the at least one of the first entity or the second entity and other entities in the network;

the degree metric is associated with a number of links associated with each node corresponding to the at least one of the first entity or the second entity and other entities in the network;

the closeness metric is associated with a path length between a node corresponding to the at least one of the first entity or the second entity and nodes corresponding to other entities in the network; and

the betweenness metric is associated with a path length between each pair of nodes.

17. The computing device of claim 13, wherein the updated location information comprises the first entity being co-located with another entity of the plurality of entities.

18. The computing device of claim 13, wherein the updated location information comprises a location being visited by the first entity for a first time.