Dynamic Recommender System

One of the foremost challenges web information systems currently confront is the effective management of large volume of documents. There is an urgent need to provide easy and swift access to the information that satisfies the needs of consumers on the web. To handle this problem web developers have focused on building information filtering systems known as Recommender Systems. Recommender Systems are the tools that assist user in navigating through the huge amount of information available on the internet. They have become an essential component of every website on the internet particularly those relating to e-commerce. However, changing user requirements pose a huge challenge in developing accurate Recommender System. Recent studies demonstrate that temporal information can play an important role in the working of Recommender System when they are deployed in dynamic real world setting. In this book, we look specifically at how to utilize temporal information as an additional input in Recommender System and provide accurate and scalable recommendations. The work focuses on the dynamics of changing user requirements with time.