Along with Kansei information being successfully introduced to information retrieval systems, particularly multimedia retrieval systems, many Kansei retrieval systems have been implemented in the past two decades. And, it has become clear that the traditional multimedia retrieval systems using key-words or/and other text information are not enough in many applications, because that they can not deal with sensitive words reflecting user’s subjectivity. In this chapter, Kansei retrieval systems efficiently taking user’s subjectivity into account will be discussed in detail. Like many traditional retrieval systems, Kansei retrieval systems are also based on databases system, which are called Kansei databases. After roughly introducing some existing Kansei retrieval systems is a general flow for designing Kansei retrieval systems. Also, we will discuss how to speed up the Kansei retrieval systems by using multidimensional indexing technologies and you will learn that our proposed multidimensional index structure, Adaptive R*-tree (AR*-tree for short), is more suitable to Kansei retrieval systems than the traditional multidimensional indexing technologies.
HD-Tree: An Efficient High-Dimensional Virtual Index Structure Using a Half Decomposition Strategy