Systems and methods for behavioural and contextual data analytics
System and method for behavioral and contextual data analytics are disclosed. An example computer system to process observational data received from a wireless device includes a memory including machine readable instructions and a processor to execute the instructions to: process the observational data to identify temporally adjacent applications to generate usage metric data, the observational data including application usage data; build a behavior model based on the identified temporally adjacent applications, the behavior model to describe user behavior associated with the wireless device; and apply the behavior model to predict a usage duration of a second application in response to usage of a first application.
1 . A computing system comprising:
a processor; and
a non-transitory computer readable storage medium, having stored thereon program instructions that, upon execution by the processor, cause performance of a set of operations comprising:
determining a plurality of usage metrics for a plurality of applications based on data collected from a plurality of wireless devices;
generating a model based on the plurality of usage metrics, the model including a plurality of nodes and a plurality of weights, respective nodes of the plurality of nodes representing users of the plurality of wireless devices, respective weights of the plurality of weights representing respective correlation coefficients between the respective nodes, the plurality of weights determined based on the plurality of usage metrics; and
determining, based on the model, a location and a status of a user of a wireless device of the plurality of wireless devices.
2 . The computing system of claim 1 , wherein the determining, based on the model, further comprises determining that the user is at a home of the user.
3 . The computing system of claim 1 , wherein the determining, based on the model, further comprises determining that the user is out of home.
4 . The computing system of claim 1 , wherein the status of the user includes at least one of:
a movement of a user; a profile status of the user of the wireless device; a length of time an application will be used by the user; or a likelihood a particular application will be used by the user.
5 . The computing system of claim 1 , wherein the determining, based on the model, the location includes determining a time indication associated with the location.
6 . The computing system of claim 5 , wherein the status of the user further corresponds to the time indication.
7 . A non-transitory computer-readable storage medium, having stored thereon program instructions that, upon execution by a processor, cause performance of a set of operations comprising:
determining a plurality of usage metrics for a plurality of applications based on data collected from a plurality of wireless devices;
generating a model based on the plurality of usage metrics, the model including a plurality of nodes and a plurality of weights, respective nodes of the plurality of nodes representing users of the plurality of wireless devices, respective weights of the plurality of weights representing respective correlation coefficients between the respective nodes, the plurality of weights determined based on the plurality of usage metrics; and
determining, based on the model, a location and status of a user of a wireless device of the plurality of wireless devices.
8 . The non-transitory computer-readable storage medium of claim 7 , wherein the determining, based on the model, the location and status of the user of the wireless device is based on a future location and a future status of the user.
9 . The non-transitory computer-readable storage medium of claim 7 , wherein the determining, based on the model, the location and status of the user of the wireless device is based on a past location and a past status of the user.
10 . The non-transitory computer-readable storage medium of claim 7 , wherein the determining, based on the model, the location and status of the user of the wireless device is based on a current location and a current status of the user.
11 . The non-transitory computer-readable storage medium of claim 7 , wherein the set of operations further comprise:
analyzing at least one of (a) respective durations of usage of the plurality of applications per time unit, (b) respective numbers of sessions of the plurality of applications per time unit, or (c) respective numbers of events associated with the plurality of applications per time unit to generate the model, the plurality of usage metrics including the at least one of the respective durations, the respective numbers of sessions, or the respective numbers of events.
12 . The non-transitory computer-readable storage medium of claim 7 , wherein a first usage metric of the plurality of usage metrics includes at least one of a usage intensity of a first one of the plurality of applications, a usage frequency of the first one of the plurality of applications, or an adoption rate of the first one of the plurality of applications, the usage intensity including at least one of a duration of usage of the first one of the plurality of applications per time unit, a number of sessions of the first one of the plurality of applications per time unit, or a number of events associated with the first one of the plurality of applications per time unit.
13 . The non-transitory computer-readable storage medium of claim 7 , the set of operations further comprising:
determining, based on the model, an advertisement that is associated with the user.
14 . A method comprising:
determining a plurality of usage metrics for a plurality of applications based on data collected from a plurality of wireless devices;
generating a model based on the plurality of usage metrics, the model including a plurality of nodes and a plurality of weights, respective nodes of the plurality of nodes representing users of the plurality of wireless devices, respective weights of the plurality of weights representing respective correlation coefficients between the respective nodes, the plurality of weights determined based on the plurality of usage metrics; and
determining, based on the model, a location of a wireless device of the plurality of wireless devices associated with a user.
15 . The method of claim 14 , wherein the determining, based on the model, further comprises determining that the user is at a home of the user.
16 . The method of claim 14 , wherein the determining, based on the model, further comprises determining that the user is out of home.
17 . The method of claim 14 , further comprising:
determining, based on the model, a status of a user of the wireless device; and
transmitting, to a third party, the location and the status of the user.
18 . The method of claim 17 , further comprising:
determining, based on the location and the status, an advertisement for the user.
19 . The method of claim 17 , wherein the status of the user includes at least one of:
a movement of a user; a profile status of the user of the wireless device; a length of time an application will be used by the user; or a likelihood a particular application will be used by the user.
20 . The method of claim 17 , wherein the determining, based on the model, the location and status of the user of the wireless device further comprises a time indication that corresponds to the location and the status of the user.