Buying preferences are captured through pre-defined algorithms programmed in the Ad Recommendation Engine. It enables enterprises to gain accurate insights related to consumer behavior. ​

Ad Recommendation Engine is trained in an algorithm which aims to provide the most relevant and accurate items to the user by filtering useful stuff from of a huge pool of data. The recommendation engine discovers data patterns in the data set by learning consumers choices and produces the outcomes that co-relates to their needs and interests. ​

For example, the engine can detect objects, backgrounds, people, animals, visible objects including what else the people are doing to what kind of apparels are people wearing – the engine processes the relevant advertisements to be displayed. The application of this could be applied at a wider range on the social medial and other areas by scanning a user profile with a set of pictures and activities.

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