Population and/or animation of spatial visualization(s)

• US 9,842,149 B2
• Filed: 03/30/2015
• Issued: 12/12/2017
• Est. Priority Date: 01/23/2012
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Inventors: Bernhardt, Daniel, Kaisser, Michael, Gulli, Antonino
• Primary Examiner(s): ALAM, SHAHID AL
• Application Number:
  US14/672,712
• Publication Number:
  US 20150205843A1
• Time in Patent Office: 988 Days
• Field of Search: 707738, 707754, 707737, 345419
• CPC Class Codes: G06F 16/248 Presentation of query results
• CPC Class Codes: G06F 16/285 Clustering or classification
• CPC Class Codes: G06F 16/287 Visualization; Browsing
• CPC Class Codes: G06F 16/9038 Presentation of query results
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 16/9536 Search customisation based on social or collaborative filtering
• CPC Class Codes: G06F 16/9538 Presentation of query results

Abstract

One or more techniques and/or systems are provided for populating and/or animating a spatial visualization, such as a map, a timeline, and/or other 2D and/or 3D visual representations of locations. The spatial visualization may be populated with events extracted from a data source (e.g., real-time events, news events, social network events, etc.), and may include relationships between events (e.g., based upon time, location, contextual similarity (e.g., social network check-in events at a restaurant), events referencing one another (e.g., an article describing a first event may comprise a hyperlink to an article describing a second event) etc.). Filter criteria (e.g., date, event type, location, etc.) may be applied to events and/or relationships when populating the spatial visualization. A sequence of events and corresponding relationships may be animated within the spatial visualization (e.g., as the events unfold over a (user) designated period of time).

Claims

1. A method for populating a spatial visualization, comprising:

receiving filter criteria comprising at least one of a date filter, a location filter, an event type filter, a relationship type filter, or a user preference filter;

extracting a filtered set of events from a data source based upon the filter criteria;

creating a temporal relationship between at least two events in the set of events, the temporal relationship based on the filter criteria;

creating a spatial relationship between at the least two events in the set of events, the spatial relationship based on the filter criteria;

populating a spatial visualization using the at least two events to create a populated spatial visualization, wherein the populated spatial visualization includes a visualization of the at least two events, the temporal relationship between the at least two events, and the spatial relationship between the at least two events; and

creating at least one of;

a referential relationship between a first event and a second event, the referential relationship identified based upon data associated with the first event comprising a reference to data associated with the second event;

or

a contextual relationship between the first event and the second event, the contextual relationship identified based upon a first event type of the first event corresponding to a second event type of the second event.

2. The method of claim 1, wherein each event of the set of extracted events includes a location, an event time, and an event type.

3. The method of claim 1, the extracting comprising:

assigning a first event type to a first event of the set of events based upon at least one of;

evaluating an event type field defined by the data source to identify the first event type;

or

executing a classification technique upon data from the data source associated with the first event to identify the first event type.

4. The method of claim 1, further comprising:

defining a first relationship type for the relationship between the first event and the second event based upon a first event type of the first event and a second event type of the second event.

5. The method of claim 1, further comprising:

defining a first relationship time for the relationship between the first event and the second event based upon a first event time of the first event and a second event time of the second event.

6. The method of claim 1, wherein the at least two events include a first event and second event, and the first event is in a:

a directed relationship with the second event.

7. The method of claim 1, the populating comprising:

representing one of the at least two events using a first symbol; and

representing another of the at least two events using a second symbol different than the first symbol.

8. The method of claim 7,

wherein the first symbol is sized according to an importance ranking.

9. The method of claim 1, comprising animating the populated spatial visualization.

10. The method of claim 1, wherein the first event type and the first event type is selected from the group consisting of:

historical events, news stories, sports events, personal events, and real-time events temporal type.

11. A system comprising a processor in electronic communication with a computer readable storage media, the computer readable storage media storing instructions that, when executed, perform a method, the method comprising:

receiving filter criteria comprising at least one of a date filter, a location filter, an event type filter, a relationship type filter, or a user preference filter;

extracting a filtered set of events from a data source based upon the filter criteria;

creating a temporal relationship between at least two events in the set of events, the temporal relationship based on the filter criteria;

creating a spatial relationship between at the least two events in the set of events, the spatial relationship based on the filter criteria;

populating a spatial visualization using the at least two events to create a populated spatial visualization, wherein the populated spatial visualization includes a visualization of the at least two events, the temporal relationship between the at least two events, and the spatial relationship between the at least two events

creating at least one of;

a referential relationship between a first event and a second event, the referential relationship identified based upon data associated with the first event comprising a reference to data associated with the second event;

or

a contextual relationship between the first event and the second event, the contextual relationship identified based upon a first event type of the first event corresponding to a second event type of the second event.

12. The system of claim 11, wherein each event of the set of extracted events includes a location, an event time, and an event type.

13. The system of claim 11, the extracting comprising:

assigning a first event type to a first event of the set of events based upon at least one of;

evaluating an event type field defined by the data source to identify the first event type;

or

executing a classification technique upon data from the data source associated with the first event to identify the first event type.

14. The system of claim 11, further comprising:

defining a first relationship type for the relationship between the first event and the second event based upon a first event type of the first event and a second event type of the second event.

15. The system of claim 11, further comprising:

defining a first relationship time for the relationship between the first event and the second event based upon a first event time of the first event and a second event time of the second event.

16. The system of claim 11, wherein the at least two events include a first event and second event, and the first event is in a directed relationship with the second event.

17. The system of claim 11, the populating comprising:

representing one of the at least two events using a first symbol; and

representing another of the at least two events using a second symbol different than the first symbol.

18. A computer readable storage device storing instructions that, when executed perform a method, the method comprising:

receiving filter criteria comprising at least one of a date filter, a location filter, an event type filter, a relationship type filter, or a user preference filter;

extracting a filtered set of events from a data source based upon the filter criteria;

creating a temporal relationship between at least two events in the set of events, the temporal relationship based on the filter criteria;

creating a spatial relationship between at the least two events in the set of events, the spatial relationship based on the filter criteria;

populating a spatial visualization using the at least two events to create a populated spatial visualization, wherein the populated spatial visualization includes a visualization of the at least two events, the temporal relationship between the at least two events, and the spatial relationship between the at least two events; and

creating at least one of;

a referential relationship between a first event and a second event, the referential relationship identified based upon data associated with the first event comprising a reference to data associated with the second event;

or

a contextual relationship between the first event and the second event, the contextual relationship identified based upon a first event type of the first event corresponding to a second event type of the second event.

19. The computer readable storage device of claim 18, wherein each event of the set of extracted events includes a location, an event time, and an event type.

20. The computer readable storage device of claim 18, the extracting comprising:

assigning a first event type to a first event of the set of events based upon at least one of;

evaluating an event type field defined by the data source to identify the first event type;

or executing a classification technique upon data from the data source associated with the first event to identify the first event type.