Haishuai Wang (with Zhenyan Ji, Weina Yao, Huaiyu Pi) is a contributing author, "A Survey of Personalized Image Retrieval and Recommendation."

Book Description: This book constitutes the thoroughly refereed proceedings of the National Conference of Theoretical Computer Science, NCTCS 2017, held in Wuhan, Hubei, China, in October 2017. The 25 full papers presented were carefully reviewed and selected from 84 submissions. They present relevant trends of current research in the area of algorithms and complexity, software theory and method, data science and machine learning theory.

Paper abstract:

With the advent of web2.0 era, it has been becoming increasingly easy to create and share Internet content. Plenty of pictures are uploaded to the Internet every day. A primary challenge against traditional image retrieval technologies is how to help users quickly discover the images they need. Personalised image retrieval is a new trend in the field of image retrieval. It not only improves the accuracy of the existing retrieval systems, but also better meets the users’ needs. Personalised image retrieval and recommendation (PIRR) can be grouped into two main categories, content-based PIRR and collaborative filtering (CF)-based PIRR. This paper first summarises the development of image retrieval and introduces different image retrieval solutions. Then the key technologies of content-based PIRR are analysed from three aspects, user interest acquisition, user interest representation and personalised implementation. Different techniques are compared and analysed. Regarding CF-based PIRR, the user-based, item-based and model-based CF-based PIRR are introduced and compared. At the end of the paper, we compare and summarise content-based PIRR and CF-based PIRR.