Feature #3: Identify Peak Interaction Times
Explore how to identify three non-overlapping peak interaction intervals on a Twitter business account by analyzing hourly user interaction data. Learn to apply sliding window techniques and dynamic programming to find the lexicographically earliest maximum sum intervals, building skills crucial for coding interviews involving array manipulation and optimization.
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Description
For this next Twitter feature, the company has decided to create an API that can be used by business accounts on Twitter. This API will identify three disjoint time intervals in which the most users followed or interacted with the businesses’ Tweets. You will be given the historical data of user interaction per hour for a particular business’ Twitter account. The API will have another parameter for hours. Your goal is to find three continuous intervals of a size equal to hours such that the sum of all the entries is the greatest. These time intervals should not overlap with each other.
Consider a Twitter profile with the following history of user interactions: [0, 2, 1, 3, 1, 7, 11, 5, 5] and hours = 2. The interaction array represents that this particular business’ account received no interactions during the first hour, 2 in the second hour, and so ...