Methods and apparatuses for context determination

• US 9,071,939 B2
• Filed: 09/23/2010
• Issued: 06/30/2015
• Est. Priority Date: 09/23/2010
• Status: Active Grant

• Current Assignee: CU Coding Limited
• Original Assignee: Nokia Technologies Oy (Nokia Corporation)
• Inventors: Hategan, Andrea, Leppanen, Jussi, Eronen, Antti
• Primary Examiner(s): MEHRA, INDER P
• Application Number:
  US13/825,670
• Publication Number:
  US 20130184007A1
• Time in Patent Office: 1,741 Days
• Field of Search: 455/405, 455/418, 455/456.1, 455/456.3
• US Class Current: 1/1
• CPC Class Codes: G06Q 30/0259 based on store location
• CPC Class Codes: G06Q 50/01 Social networking
• CPC Class Codes: H04W 4/025 using location based information parameters

Abstract

Methods and apparatuses are provided for context determination. A method may include determining a location identifier. The location identifier may be indicative of a location of an apparatus. The method may further include determining a location cluster based at least in part on the location identifier. The method may additionally include determining a first probability for each of one or more contexts based at least in part on the determined location cluster. The method may also include determining a context of the apparatus based at least in part on the determined first probability. Corresponding apparatuses are also provided.

Claims

1. A method comprising:

determining a location identifier, the location identifier being indicative of a location of an apparatus;

determining a location cluster based at least in part on the location identifier, wherein the determined location cluster comprises a location cluster determined from a set of at least one location cluster, and wherein each location cluster in the set of at least one location cluster comprises a cluster of one or more location identifiers grouped based at least in part on historically observed context data comprising a plurality of location identifiers augmented with context labels corresponding to observed contexts of the apparatus;

determining a first probability for one or more contexts based at least in part on the determined location identifier, wherein determining the first probability comprises determining the first probability for one or more contexts based at least in part on the determined location cluster; and

determining a context of the apparatus based at least in part on the determined first probability.

2. The method of claim 1, further comprising:

determining sensory data; and

determining a second probability for one or more contexts based at least in part on the sensory data; and

wherein determining a context of the apparatus comprises determining the context of the apparatus further based on the determined second probability.

3. The method of claim 2, wherein determining a context of the apparatus comprises:

combining the first probability and the second probability for one or more contexts to determine a combined probability for the one or more contexts; and

determining the context of the one or more contexts having the greatest combined probability.

4. The method of claim 1, wherein:

determining a location cluster comprises determining a location cluster from the set of at least one location cluster that includes the determined location identifier; and

determining a first probability for one or more contexts comprises determining a predicted probability for a context based at least in part on a distribution of context labels for the determined location cluster.

5. The method of claim 4, further comprising:

determining a distance between the determined location cluster and a second location cluster;

comparing the determined distance to a predefined threshold distance; and

merging the determined location cluster and the second location cluster in an instance in which the determined distance is less than the threshold distance.

6. The method of claim 4, further comprising:

determining a context label having a greatest probability for the determined location cluster;

comparing the determined context label to a context label having a greatest probability for a second location cluster; and

merging the determined location cluster and the second location cluster in an instance in which the determined context label and the context label having the greatest probability for the second location cluster match.

7. The method of claim 6, further comprising:

selecting a number of location clusters to be formed; and

forming the selected number of location clusters.

8. An apparatus comprising at least one processor and at least one memory storing computer program code, wherein the at least one memory and stored computer program code are configured, with the at least one processor, to cause the apparatus to at least:

determine a location identifier, the location identifier being indicative of a location of the apparatus;

determine a location cluster based at least in part on the location identifier, wherein the determined location cluster comprises a location cluster determined from a set of at least one location cluster, and wherein each location cluster in the set of at least one location cluster comprises a cluster of one or more location identifiers grouped based at least in part on historically observed context data comprising a plurality of location identifiers augmented with context labels corresponding to observed contexts of the apparatus;

determine a first probability for one or more contexts based at least in part on the determined location identifier and the determined location cluster; and

determine a context of the apparatus based at least in part on the determined first probability.

9. The apparatus of claim 8, wherein the at least one memory and stored computer program code are configured, with the at least one processor, to further cause the apparatus to:

determine sensory data; and

determine a second probability for one or more contexts based at least in part on the sensory data; and

wherein the at least one memory and stored computer program code are configured, with the at least one processor, to cause the apparatus to determine a context of the apparatus by determining the context of the apparatus further based on the determined second probability.

10. The apparatus of claim 9, wherein the at least one memory and stored computer program code are configured, with the at least one processor, to cause the apparatus to determining a context of the apparatus at least in part by:

combining the first probability and the second probability for one or more contexts to determine a combined probability for the one or more contexts; and

determining the context of the one or more contexts having the greatest combined probability.

11. The apparatus of claim 8, wherein the at least one memory and stored computer program code are configured, with the at least one processor, to cause the apparatus to:

determine a location cluster at least in part by determining a location cluster from the set of at least one location cluster that includes the determined location identifier; and

determine a first probability for one or more contexts at least in part by determining a predicted probability for a context based at least in part on a distribution of context labels for the determined location cluster.

12. The apparatus of claim 11, wherein the at least one memory and stored computer program code are configured, with the at least one processor, to further cause the apparatus to:

determine a distance between the determined location cluster and a second location cluster;

compare the determined distance to a predefined threshold distance; and

merge the determined location cluster and the second location cluster in an instance in which the determined distance is less than the threshold distance.

13. The apparatus of claim 11, wherein the at least one memory and stored computer program code are configured, with the at least one processor, to further cause the apparatus to:

determine a context label having a greatest probability for the determined location cluster;

compare the determined context label to a context label having a greatest probability for a second location cluster; and

merge the determined location cluster and the second location cluster in an instance in which the determined context label and the context label having the greatest probability for the second location cluster match.

14. The apparatus of claim 13, wherein the at least one memory and stored computer program code are configured, with the at least one processor, to further cause the apparatus to:

select a number of location clusters to be formed; and

form the selected number of location clusters.

15. A computer program product comprising at least one non-transitory computer-readable storage medium having computer-readable program instructions stored therein, the computer-readable program instructions comprising:

program instructions configured to determine a location identifier, the location identifier being indicative of a location of an apparatus;

program instructions configured to determine a location cluster based at least in part on the location identifier, wherein the determined location cluster comprises a location cluster determined from a set of at least one location cluster, and wherein each location cluster in the set of at least one location cluster comprises a cluster of one or more location identifiers grouped based at least in part on historically observed context data comprising a plurality of location identifiers augmented with context labels corresponding to observed contexts of the apparatus;

program instructions configured to determine a first probability for one or more contexts based at least in part on the determined location identifier, wherein the program instructions configured to determine the first probability comprise program instructions configured to determine the first probability for one or more contexts based at least in part on the determined location cluster; and

program instructions configured to determine a context of the apparatus based at least in part on the determined first probability.

16. The computer program product of claim 15, further comprising:

program instructions configured to determine sensory data; and

program instructions configured to determine a second probability for one or more contexts based at least in part on the sensory data; and

wherein the program instructions configured to determine a context of the apparatus comprise program instructions configured to determine the context of the apparatus further based on the determined second probability.