As usual, our ideation team started brainstorming to validate the features and its contribution to the app's intended purpose. On successful validation, feature enhancements were discussed to deliver the best for the next big thing in the 'News & Magazine' category.
Since one of the main features of this app is to help the user digest the news even in the shortest free time one could have, we were more cautious in delivering the best User Experience possible within the limitations of this application.
The Google Calendar integration system was developed to look for the free time of the user between his scheduled plans. An extension of this feature will be analyzing the users' usual commuting times through public transport for the articles to be delivered and the ones through self-driving commute when the articles won't be prompted for reading.
For example, when a user has 10 mins of free time, one or more news articles that could be read well within 10mins alone will be suggested. The user's reading speed data will be analyzed to further deliver the right articles just not to leave reading a news midway.
For the curation algorithms, Python Pandas was used by the developers with the help of existing datasets available with the client. Provisions were made to let the user 'Thumbs-up' or 'Thumbs-down' the article shown to him. Based on the user's feedback the algorithm learns by itself to improve the suggestion accuracy. In the long run, the users will be segmented and tagged based on the common characteristic models they share.