Device identifier similarity models derived from online event signals

摘要

A computerized method and system operable to build a device identifier similarity model with online event signals and determine similar network device identifiers. A processing circuit receives a first set of network device identifiers. The processing circuit represents each network device identifier of the first set by feature data associated with each network device identifier's network activity, where the feature data is associated with the content clicked-on or converted-on. The processing circuit applies abstractions on the feature data to form concepts. The processing circuit derives at least one hierarchy of feature data based on the keywords and concepts of the feature data. The processing circuit expands the feature data based on the derived at least one hierarchy of feature data and generates the device identifier similarity model based on the expanded feature data. The processing circuit is also capable of determining long-term and short-term history events.

主权项

1. A computerized method of building a device identifier similarity model with online event signals, the method comprising:
receiving at a processing circuit a first set of network device identifiers; identifying, by the processing circuit, an online event associated with network activity of each network device identifier of the first set; identifying, using the processing circuit, for each network device identifier of the first set, one or more long-term browsing history events surrounding the identified online event based on the network device identifier's network activity, the long-term browsing history events corresponding to events occurring prior to a first time from the identified online event; identifying, using the processing circuit, for each network device identifier of the first set, one or more short-term browsing history events surrounding the identified online event based on the network device identifier's network activity, the short-term browsing history events corresponding to events occurring after the first time from the identified online event; representing, using the processing circuit, each device identifier of the first set as a vector based on feature data corresponding to each network device identifier's network activity, the feature data comprising keywords corresponding to content associated with the device identifier's network activity; applying, using the processing circuit, abstractions on the feature data to form concepts, wherein each concept represents a category of interest; deriving, using the processing circuit, at least one hierarchy of the feature data based on the keywords and concepts of the feature data; expanding, using the processing circuit, the feature data based on the derived at least one hierarchy of the feature data; applying, using the processing circuit, a clustering algorithm on each of the vectors to identify a plurality of clusters of device identifiers that share a common interest; providing, using the processing circuit, at least one subset of network device identifiers corresponding to each of the plurality of cluster; and generating, using the processing circuit, the device identifier similarity model based on the expanded feature data.