Dynamic Ranking of Personalized Recommendations using Cosine Similarity and User Ratings

Finding an experienced person to guide a youngster to support in building their career or getting help from a young mind for and experienced person to support them with ever-changing technologies is not an easy task. Hence, many are facing issues in getting the right support at the right time. A very experienced non-technical businessman may need support from a youngster with strong technical skills may be for cloud support to ensure the growth of the company is not hindered. The solution to this problem is to develop a mobile application that creates an interface between retired people and youngsters such that both domains of people get the recommendation of the most suitable list of people belonging to other domain based on cosine similarity between the profile vectors of two people and the ranking of the displayed list of people is dynamically updated based on the multi-criterion rating given by other users to people in the list. Here both the retired people and the youngsters who wish to provide support are termed as supporters and the people who desire to get support are termed as users. This reduces the work of users because they need not explicitly search for the people who are most suitable for providing support for them, they automatically get the recommendations, also the supporters can generate revenue. The application also allows the user to chat with supporters regarding any further issues by linking WhatsApp with the mobile application.