| dc.description.abstract | For OTT media streaming products like VIU, it is really important to increase the consumption of media content as much as possible. To get the highest benefit, the user must stay on the platform and consume numerous content. To survive in markets where too many competitors are there as the Indian market, this problem is essential to resolve. The problem is to increase the engagement time between the customer and platform, which can be solved by augmenting the content selection. To solve the problem, the company should customize its homepage in favour of user appealing content. Also, the system must behave dynamically as all users have a different preference. By executing this approach, we can improve the engagement time of the users, and hence solved our problem. CAL is the solution to our problem, and it manages all the issues that we had in the past. Now, the users will get the preferred content from the combination of various content selectors, which can select content based on user preference. Trending APIs, recommendation APIs, and BecauseYouHaveWatched APIs are known as content selectors which used for generating intelligent content selection for the user. We are trying to build a system that will give intelligent and flexible content selection. It aims for flexible consumption patterns. It supports plug and plays models for additional content selection algorithms which means no need for updating the system when new content selector service will join the system in the future. To provide the plug and play feature, the use of a discovery service is necessary. I have developed the content selector registry, which is a discovery service API. It manages the availability of the content selector that resides inside the Kubernetes cluster. Also, written a Google Cloud Function that will store the data to BigQuery by initiating the DataFlow. Later the Data of BigQuery will use to generate Insights and KPI metrics. | |
