Interactive personalized recommendation systems for human health

A sequential recommendation approach for interactive personalized story generation

In story-based games or other interactive story systems, a Drama Manager is an omniscient agent that acts to bring about a particular sequence of plot points for the user to experience. We present a Drama Manager that uses player modeling to personalize the user’s story according to his or her storytelling preferences. In order to deliver personalized stories, a Drama Manager must make decision...

Effective Personalized Recommendation in Collaborative Tagging Systems

Recently, collaborative tagging systems have attracted more and more attention and have been widely applied in web systems. Tags provide highly abstracted information about personal preferences and item content, and are therefore potential to help in improving better personalized recommendations. In this paper, we propose a tag-based recommendation algorithm considering the personal vocabulary ...

An Interactive Personalized Recommendation System Using the Hybrid Algorithm Model

With the rapid development of e-commerce, the contradiction between the disorder of business information and customer demand is increasingly prominent. This study aims to make ecommerce shopping more convenient, and avoid information overload, by an interactive personalized recommendation system using the hybrid algorithm model. The proposed model first uses various recommendation algorithms to...

Personalized Search and Recommendation for Health Information Resources

Web-based Recommendation Systems for Personalized e-Commerce Shopping

In an e-commerce environment, personalization has taken on an important role in improving service levels, and fostering customer loyalty. In addition, the recommendation systems techniques that support many personalization systems are capable of customizing the recommendation of products and the display of advertisements to the individual level. This chapter provides a review of the major recom...