"Ad you like it": advertisement sourcing and selection technique across multiple heterogeneous applications

Sourcing and selection of online advertisement is done with the objective of streaming advertisements that match user's interests and internet surfing habits. Choosing relevant advertisements that bring user's focus and attention have higher click rate. Innovative concepts, such as crawling recently surfed web pages (or websites), user's (or web portal server) geographical location, user's profile, age, gender, and surfing habits., have been used to identify most relevant advertisements. However, selecting and streaming an advertisement that exactly matches user's interest continues to be a challe. This paper proposes and shares an innovative technique that significantly helps in mapping user's interest quotient to streamed advertisements. This technique respects the individuality of a user and is able to differentiate between users. The proposed solution is implemented by enabling communication channels across multiple heterogeneous user-initiated applications. Applications that do not directly communicate with advertisement data sources, leverage other application running on the same user's account and submit their own metadata to the applications attached to advertisement data sources. The proposed paper helps in substituting publisher's assumptions of a user's interest with real-time user's objects of interest.