Mobile users spend an extensive amount of time on ty**. A more efficient text input
instrument brings a significant enhancement of user experience. Deep learning techniques …

Recommender systems aim to forecast users' rank, interests, and preferences in specific
products and recommend them to a user for purchase. Collaborative filtering is the most …

With the convergence of the era of global news and the era of big data, the daily amount of
news sent to the world is exploding. Users also face the problem of information overloads …

Because of the popularity of Internet and mobile Internet, people are facing serious
information overloading problems nowadays. Recommendation engine is very useful to help …

In collaborative filtering recommender systems, items recommended to an active user are
selected based on the interests of users similar to him/her. Collaborative filtering systems …

随着互联网和信息计算的飞速发展, 衍生了海量数据, 我们已经进入信息爆炸的时代.
网络中各种信息量的指数型增长导致用户想要从大量信息中找到自己需要的信息变得越来越 …

Identifying users with similar interest plays a vital role in building the recommendation
model. Web server log acts as a repository from which the information needed for identifying …