Device tagging using micro-location movement data

1. A method comprising:

computing, using a processor and a memory, from a collection of movement data of a device, a pattern of movement of the device in a venue during a period;

evaluating whether the pattern fits a profile from a set of profiles, each profile in the set of profiles comprising a set of characteristics of a different type of user; and

adding to a data record in the collection of movement data of the device, responsive to the pattern fitting the profile from the set of profiles, a label of the profile indicative of a type of a user associated with the device.

2. The method of claim 1 , further comprising:

constructing the set of profiles, wherein a common characteristic is defined to have a first range of values in the profile, and wherein the common characteristic is defined to have a different range of values in a second profile, the first range of the characteristic causing the profile to correspond to a first type of user and the second range of the characteristic causing the second profile to correspond to a second type of user.

3. The method of claim 1 , further comprising:

determining, as a part of the evaluating whether the pattern fits the profile, whether a set of patterns computed from the pattern are within a subset of ranges, the subset of ranges being specified for a subset of characteristics in the profile, the evaluating being affirmative when the subset of characteristics is at least a threshold proportion of the set of characteristics in the profile.

4. The method of claim 1 , wherein the pattern fits the profile because the pattern matches a range specified for the characteristic in the profile.

5. The method of claim 1 , further comprising:

performing, as a part of the evaluating, a contextual analysis relative to the profile, wherein the contextual analysis uses a past movement data of the device.

6. The method of claim 1 , further comprising:

performing, as a part of the evaluating, a cognitive analysis relative to the profile, wherein the cognitive analysis uses a knowledgebase of human behavior information to determine a cognitive state of the user of the mobile device, wherein the profile comprises a cognitive characteristic.

7. The method of claim 1 , further comprising:

operating a micro-location beacon to collect the movement data from the device.

8. A computer usable program product comprising one or more computer-readable storage devices, and program instructions stored on at least one of the one or more storage devices, the stored program instructions comprising:

program instructions to compute, using a processor and a memory, from a collection of movement data of a device, a pattern of movement of the device in a venue during a period;

program instructions to evaluate whether the pattern fits a profile from a set of profiles, each profile in the set of profiles comprising a set of characteristics of a different type of user; and

program instructions to add to a data record in the collection of movement data of the device, responsive to the pattern fitting the profile from the set of profiles, a label of the profile indicative of a type of a user associated with the device.

9. The computer usable program product of claim 8 , further comprising:

program instructions to construct the set of profiles, wherein a common characteristic is defined to have a first range of values in the profile, and wherein the common characteristic is defined to have a different range of values in a second profile, the first range of the characteristic causing the profile to correspond to a first type of user and the second range of the characteristic causing the second profile to correspond to a second type of user.

10. The computer usable program product of claim 8 , further comprising:

program instructions to determine, as a part of the evaluating whether the pattern fits the profile, whether a set of patterns computed from the pattern are within a subset of ranges, the subset of ranges being specified for a subset of characteristics in the profile, the evaluating being affirmative when the subset of characteristics is at least a threshold proportion of the set of characteristics in the profile.

11. The computer usable program product of claim 8 , wherein the pattern fits the profile because the pattern matches a range specified for the characteristic in the profile.

12. The computer usable program product of claim 8 , further comprising:

program instructions to perform, as a part of the evaluating, a contextual analysis relative to the profile, wherein the contextual analysis uses a past movement data of the device.

13. The computer usable program product of claim 8 , further comprising:

program instructions to perform, as a part of the evaluating, a cognitive analysis relative to the profile, wherein the cognitive analysis uses a knowledgebase of human behavior information to determine a cognitive state of the user of the mobile device, wherein the profile comprises a cognitive characteristic.

14. The computer usable program product of claim 8 , further comprising:

program instructions to operate a micro-location beacon to collect the movement data from the device.

15. The computer usable program product of claim 8 , wherein the computer usable code is stored in a computer readable storage device in a data processing system, and wherein the computer usable code is transferred over a network from a remote data processing system.

16. The computer usable program product of claim 8 , wherein the computer usable code is stored in a computer readable storage device in a server data processing system, and wherein the computer usable code is downloaded over a network to a remote data processing system for use in a computer readable storage device associated with the remote data processing system.

17. A computer system comprising one or more processors, one or more computer-readable memories, and one or more computer-readable storage devices, and program instructions stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, the stored program instructions comprising:

program instructions to compute, from a collection of movement data of a device, a pattern of movement of the device in a venue during a period;

program instructions to evaluate whether the pattern fits a profile from a set of profiles, each profile in the set of profiles comprising a set of characteristics of a different type of user; and

program instructions to add to a data record in the collection of movement data of the device, responsive to the pattern fitting the profile from the set of profiles, a label of the profile indicative of a type of a user associated with the device.

18. The computer system of claim 17 , further comprising:

program instructions to construct the set of profiles, wherein a common characteristic is defined to have a first range of values in the profile, and wherein the common characteristic is defined to have a different range of values in a second profile, the first range of the characteristic causing the profile to correspond to a first type of user and the second range of the characteristic causing the second profile to correspond to a second type of user.

19. The computer system of claim 17 , further comprising:

program instructions to determine, as a part of the evaluating whether the pattern fits the profile, whether a set of patterns computed from the pattern are within a subset of ranges, the subset of ranges being specified for a subset of characteristics in the profile, the evaluating being affirmative when the subset of characteristics is at least a threshold proportion of the set of characteristics in the profile.

20. The computer system of claim 17 , wherein the pattern fits the profile because the pattern matches a range specified for the characteristic in the profile.