Trajectory Data Surfacing System: Surfacing Useful and Relevant Entity Annotations

• US 20100082611A1
• Filed: 09/23/2008
• Published: 04/01/2010
• Est. Priority Date: 09/23/2008
• Status: Abandoned Application

• Current Assignee: Excalibur IP, LLC (Acacia Research Corporation)
• Original Assignee: Yahoo! Inc. (Apollo Global Management, Inc.)
• Inventors: Churchill, Elizabeth Frances, Jones, Michael Cameron, Athsani, Athellina
• Application Number:
  US12/236,353
• Publication Number:
  US 20100082611A1
• Time in Patent Office: Days
• US Class Current: 707/724
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising

Abstract

Multiple entities are tracked over periods of time and information concerning these entities are collected. For each entity, the entities associated with the entity and the types of associations are determined. One or more entities of interest is/are identified. Different weights are assigned to the entities on the trajectories connecting with the entity or entities of interest based on their associations with the entity or entities of interest and their positions on the trajectories. Selected entities are ranked and surfaced based on their total weights for the entity or entities of interest.

Claims

1. A method, comprising:

identifying associations among selected ones of a plurality of entities;

identifying an entity of interest from the plurality of entities;

assigning weights to entities on trajectories that connect with the entity of interest based on their associations with the entity of interest and their positions on the trajectories; and

ranking selected entities on the trajectories for the entity of interest based on their weights.

2. A method as recited in claim 1, wherein when assigning weights to entities on trajectories that connect with the entity of interest, if a first entity has a closer association with the entity of interest than a second entity, then the first entity is assigned a relatively higher weight than the second entity.

3. A method as recited in claim 1, wherein when assigning weights to entities on trajectories that connect with the entity of interest, if a third entity has a newer association with the entity of interest than a fourth entity, then the third entity is assigned a relatively higher weight than the fourth entity.

4. A method as recited in claim 1, wherein when assigning weights to entities on trajectories that connect with the entity of interest, if a fifth entity and a sixth entity are on the same trajectory and the fifth entity is closer to the entity of interest than the sixth entity, then the fifth entity is assigned a relatively higher weight than the sixth entity.

5. A method as recited in claim 1, wherein when assigning weights to entities on trajectories that connect with the entity of interest, if a seventh entity has a greater number of associations with the entity of interest than an eight entity, then the seventh entity is assigned a relatively higher weight than the eighth entity.

6. A method as recited in claim 1, wherein when assigning weights to entities on trajectories that connect with the entity of interest, a weight assigned to a ninth entity not directly connected with the entity of interest is affected by weight assigned to at least one entity in between the ninth entity and the entity of interest on a trajectory connecting the ninth entity and the entity of interest.

7. A method as recited in claim 1, further comprising:

tracking the plurality of entities; and

collecting information concerning the plurality of entities.

8. A method as recited in claim 7, further comprising:

aggregating the information concerning the plurality of entities,

wherein the information is used to identify the associations among the selected ones of the plurality of entities.

9. A method as recited in claim 1, further comprising:

categorizing the plurality of entities and their associations.

10. A method as recited in claim 1, further comprising:

applying a context filter to the plurality of entities and their associations.

11. A method as recited in claim 1, further comprising:

receiving a new weight for an entity from a user;

receiving a modification of a weight for an entity from a user; and

receiving a deletion of a weight for an entity from a user.

12. A computer program product comprising a computer-readable medium having a plurality of computer program instructions stored therein, which are operable to cause at least one computing device to:

identify associations among selected ones of a plurality of entities;

identify an entity of interest from the plurality of entities;

assign weights to entities on trajectories that connect with the entity of interest based on their associations with the entity of interest and their positions on the trajectories; and

rank selected entities on the trajectories for the entity of interest based on their total weights.

13. A computer program product as recited in claim 12, wherein when assign weights to entities on trajectories that connect with the entity of interest, if a first entity has a closer association with the entity of interest than a second entity, then the first entity is assigned a relatively higher weight than the second entity.

14. A computer program product as recited in claim 12, wherein when assign weights to entities on trajectories that connect with the entity of interest, if a third entity has a newer association with the entity of interest than a fourth entity, then the third entity is assigned a relatively higher weight than the fourth entity.

15. A computer program product as recited in claim 12, wherein when assign weights to entities on trajectories that connect with the entity of interest, if a fifth entity and a sixth entity are on the same trajectory and the fifth entity is closer to the entity of interest than the sixth entity, then the fifth entity is assigned a relatively higher weight than the sixth entity.

16. A computer program product as recited in claim 12, wherein when assign weights to entities on trajectories that connect with the entity of interest, if a seventh entity has a greater number of associations with the entity of interest than an eight entity, then the seventh entity is assigned a relatively higher weight than the eighth entity.

17. A computer program product as recited in claim 12, wherein when assign weights to entities on trajectories that connect with the entity of interest, a weight assigned to a ninth entity not directly connected with the entity of interest is affected by weight assigned to at least one entity in between the ninth entity and the entity of interest on a trajectory connecting the ninth entity and the entity of interest.

18. A computer program product as recited in claim 12, the plurality of computer program instructions are further operable to:

apply a context filter to the plurality of entities and their associations.

19. A computer program product as recited in claim 12, wherein the plurality of computer program instructions are further operable to:

categorize the plurality of entities and their associations, wherein the weights assigned to the entities with respect to the entity of interest are determined based on the categories of their associations.

20. A computer program product as recited in claim 12, wherein the plurality of computer program instructions are further operable to:

receive a new weight for an entity from a user;

receive a modification of a weight for an entity from a user; and

receive a deletion of a weight for an entity from a user.