Framework for social tag recommendation using Lion Optimization Algorithm and collaborative filtering techniques

摘要

Recommendation systems have been paying attention as gaining a much important character with the growth of data mining with collaborative filtering (CF) techniques. With a specific end goal to perform better recommendation data mining and collaborative filtering methodologies are used these days. The most favourite technique behind the success of the recommendation system was collaborative filtering. CF promise the interested of an active user supported on the sentiment of users with correspondent interests. Data mining techniques lead to the reduction of huge data set into smaller data set in which all the services are similar to one another. To recommend social tag we proposed a framework that is combining the data mining techniques such as feature selection and clustering with collaborative filtering algorithms. In this paper lion optimization technique are utilized for feature selection and clustering and it was hybridized with slope one algorithm. At long last, this calculation is contrasted and slope one calculation and the execution is dissected by utilizing the measurements such as precision, recall, mean absolute error and root mean square error.