Computing system and methods for associating computing devices
Certain implementations of the disclosed technology may include computing systems and methods for associating computing devices. According to an example implementation, a computer-implemented method is provided. The method may include determining a first set of content items associated with a first computing device and determining a second set of content items associated with a second computing device. The method may also include determining whether the first and second computing devices constitute a candidate pair. The method may also include calculating s similarity metric between the first and second computing devices based on a common set of content items shared between the devices. Finally, the method may include associating the first and second computing devices with one another.
1. A computer-implemented method comprising:
determining, by a processor, a first set of content items that have been accessed on a first computing device within the first predetermined timeframe;
determining, by the processor, a second set of content items that have been accessed on a second computing device within the first predetermined timeframe;
calculating, by the processor, a frequency score for each content item of the first set of content items and the second set of content items, each frequency score representing a frequency with which a given content item has been accessed over the first predetermined timeframe across the first and second computing devices;
determining, by the processor, whether the first computing device and the second computing device constitute a candidate pair of computing devices, by determining whether the first computing device and the second computing device have utilized the same public IP address within a second, predetermined timeframe;
in response to determining that the first computing device and second computing device constitute a candidate pair of computing devices, calculating, by the processor, a similarity metric between the first computing device and the second computing device based at least on the calculated frequency score for each content item, wherein the calculation of the similarity metric includes weighting each content item based on its frequency score such that content items not frequently accessed are given a weight higher than content items frequently accessed; and
in response to determining that the calculated similarity metric exceeds a predetermined threshold, associating, by the processor, the first computing device and the second computing device with one another as used by a single individual.
2. The computer-implemented method of claim 1 , wherein determining whether the first computing device and the second computing device constitute the candidate pair of computing devices comprises determining whether the first computing device and the second computing device have been detected within a predetermined spatial vicinity of one another at any point in time.
3. The computer-implemented method of claim 1 , further comprising:
generating digital content based on the association between the first computing device and the second computing device; and
transmitting the generated digital content to at least one of the first computing device and the second computing device.
4. The computer-implemented method of claim 1 , wherein the content items comprise at least one of:
applications;
web sites;
images; and
videos.
5. The computer-implemented method of claim 1 , wherein associating the first computing device and the second computing device with one another comprises at least one of:
updating an index identifying the first and second computing devices as being associated with one another;
generating a first pointer from data describing the first computing device to data describing the second computing device; and
generating a second pointer from data describing the second computing device to data describing the first computing device.
6. A computing system comprising:
memory comprising executable instructions; and
a processor operatively connected to the memory, the processor configured to execute the executable instructions in order to effectuate a method comprising:
determining a first set of content items that have been accessed on a first computing device within a first predetermined timeframe;
determining a second set of content items that have been accessed on a second computing device within a first predetermined timeframe;
calculating, by the processor, a frequency score for each content item of the first set of content items and the second set of content items, each frequency score representing a frequency with which a given content item has been accessed over the first predetermined timeframe across the first and second computing devices;
determining whether the first computing device and the second computing device constitute a candidate pair of computing devices, by determining whether the first computing device and the second computing device have utilized the same public IP address within a second predetermined timeframe;
in response to determining that the first computing device and second computing device constitute a candidate pair of computing devices, calculating a similarity metric between the first computing device and the second computing device based at least on the calculated frequency score for each content item, wherein the calculation of the similarity metric includes weighting each content item based on its frequency score such that content items not frequently accessed are given a weight higher than content items frequently accessed; and
in response to determining that the calculated similarity metric exceeds a predetermined threshold, associating the first computing device and the second computing device with one another as used by a single individual.
7. A non-transitory computer-readable medium comprising executable instructions that when executed by a processor cause the processor to effectuate a method comprising:
determining a first set of content items that have been accessed on a first computing device within a first predetermined timeframe;
determining a second set of content items that have been accessed on a second computing device within the first predetermined timeframe;
calculating a frequency score for each content item of the first set of content items and the second set of content items, each frequency score representing a frequency with which a given content item has been accessed over the first predetermined timeframe across the first and second computing devices;
determining whether the first computing device and the second computing device constitute a candidate pair of computing devices, by determining whether the first computing device and the second computing device have utilized the same public IP address within a second predetermined timeframe;
in response to determining that the first computing device and second computing device constitute a candidate pair of computing devices, calculating a similarity metric between the first computing device and the second computing device based at least on the calculated frequency score for each content item, wherein the calculation of the similarity metric includes weighting each content item based on its frequency score such that content items not frequently accessed are given a weight higher than content items frequently accessed; and
in response to determining that the calculated similarity metric exceeds a predetermined threshold, associating the first computing device and the second computing device with one another as used by a single individual.