Analysis of critical aspects to attract online contents

Web portal sites have become an important medium to deliver digital content and service to the users such as news, advertisements, and so on. It's necessary to design a recommender system to attract more number of users on particular content module. To address this challenge, in this paper we propose deeper user action interpretation to enhance those critical aspects. Interpreting users' actions from the factors of user engagement to achieve estimation of content attractiveness. To attract the online content, estimate the rank for the content modules then, when a particular content module is ranked with same number, the server is being got confused to process the request of the user. The drawback is lack of data, traffic and unpredictable result which requested by the user to overcome this problem introducing association rule mining algorithm.