TEMPORAL ANOMALY DETECTION SYSTEM AND METHOD
A method, a system, and an article are provided for detecting and managing anomalies associated with content presentations. An example computer-implemented method can include: obtaining data including a history of content presentations by a plurality of publishers on a plurality of client devices; calculating a plurality of performance indicators for each publisher based on the data, the performance indicators providing a measure of user interactions with the content presented by the publisher; generating a time history of each performance indicator for each of a plurality of time periods; selecting, for each time history, at least one anomaly detector from a plurality of anomaly detectors; detecting an anomaly in at least one time history using the selected at least one anomaly detector; and based on the detected anomaly, facilitating an adjustment of content presentations by the plurality of publishers.
1 . A computer-implemented method, comprising:
obtaining data comprising a history of content presentations by a plurality of publishers on a plurality of client devices;
calculating a plurality of performance indicators for each publisher based on the data, the performance indicators comprising a measure of user interactions with the content presented by the publisher;
generating a time history of each performance indicator for each of a plurality of time periods;
selecting, for each time history, at least one anomaly detector from a plurality of anomaly detectors;
detecting an anomaly in at least one time history using the selected at least one anomaly detector; and
based on the detected anomaly, facilitating an adjustment of content presentations by the plurality of publishers.
2 . The method of claim 1 , wherein each publisher comprises at least one of a website and a software application.
3 . The method of claim 1 , wherein the content comprises at least one of an image, a video, audio, a computer game, and any combination thereof.
4 . The method of claim 1 , wherein the performance indicators comprise at least one of a number of content presentations, a number of clicks on the content presentations, a number of software application installations related to the content presentations, and a click-to-install ratio.
5 . The method of claim 1 , wherein the time periods comprise at least one of an hour, a day, and a week.
6 . The method of claim 1 , wherein detecting the anomaly comprises:
determining a baseline for the at least one time history; and
determining a difference between the at least one time history and the baseline.
7 . The method of claim 1 , wherein detecting the anomaly comprises determining that the at least one time history comprises a statistically significant deviation.
8 . The method of claim 1 , wherein the anomaly comprises fraud.
9 . The method of claim 1 , wherein facilitating the adjustment comprises revoking an authorization for at least one publisher to present content.
10 . The method of claim 1 , wherein facilitating the adjustment comprises adjusting a volume of content presented by at least one publisher.
11 . A system, comprising:
one or more computer processors programmed to perform operations comprising:
obtaining data comprising a history of content presentations by a plurality of publishers on a plurality of client devices;
calculating a plurality of performance indicators for each publisher based on the data, the performance indicators comprising a measure of user interactions with the content presented by the publisher;
generating a time history of each performance indicator for each of a plurality of time periods;
selecting, for each time history, at least one anomaly detector from a plurality of anomaly detectors;
detecting an anomaly in at least one time history using the selected at least one anomaly detector; and
based on the detected anomaly, facilitating an adjustment of content presentations by the plurality of publishers.
12 . The system of claim 11 , wherein each publisher comprises at least one of a website and a software application.
13 . The system of claim 11 , wherein the content comprises at least one of an image, a video, audio, a computer game, and any combination thereof.
14 . The system of claim 11 , wherein the performance indicators comprise at least one of a number of content presentations, a number of clicks on the content presentations, a number of software application installations related to the content presentations, and a click-to-install ratio.
15 . The system of claim 11 , wherein detecting the anomaly comprises:
determining a baseline for the at least one time history; and
determining a difference between the at least one time history and the baseline.
16 . The system of claim 11 , wherein detecting the anomaly comprises determining that the at least one time history comprises a statistically significant deviation.
17 . The system of claim 11 , wherein the anomaly comprises fraud.
18 . The system of claim 11 , wherein facilitating the adjustment comprises revoking an authorization for at least one publisher to present content.
19 . The system of claim 11 , wherein facilitating the adjustment comprises adjusting a volume of content presented by at least one publisher.
20 . An article, comprising:
a non-transitory computer-readable medium having instructions stored thereon that, when executed by one or more computer processors, cause the computer processors to perform operations comprising:
obtaining data comprising a history of content presentations by a plurality of publishers on a plurality of client devices;
calculating a plurality of performance indicators for each publisher based on the data, the performance indicators comprising a measure of user interactions with the content presented by the publisher;
generating a time history of each performance indicator for each of a plurality of time periods;
selecting, for each time history, at least one anomaly detector from a plurality of anomaly detectors;
detecting an anomaly in at least one time history using the selected at least one anomaly detector; and
based on the detected anomaly, facilitating an adjustment of content presentations by the plurality of publishers.