DocumentCode
2251333
Title
A Similarity Search Approach to Solving the Multi-query Problems
Author
Shi, Yong ; Graham, Brian
Author_Institution
Dept. of Comput. Sci., Kennesaw State Univ., Kennesaw, GA, USA
fYear
2012
fDate
May 30 2012-June 1 2012
Firstpage
237
Lastpage
242
Abstract
In this paper, we present our research on similarity search problems. Similarity search problems define the distances between data points and a given query point Q, efficiently and effectively selecting data points which are closest to Q. It can be applied in various data mining fields. In many applications, information similar to multiple queries is required. In this paper, we explore the meaning of K nearest neighbors from a new perspective, define the distance between a data point and a query point set, and propose an algorithm to find nearest neighbors to multiple queries with possibly different degrees of importance. Our approach works for both full similarities and partial similarities in subsets of dimensions.
Keywords
data mining; learning (artificial intelligence); query processing; set theory; K nearest neighbors; data mining fields; data point selection; multiquery problems; query point set; similarity search problems; Algorithm design and analysis; Indexes; Measurement; Nearest neighbor searches; Search problems; Signal processing algorithms; KNN; Multi-query; Similarity Search;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer and Information Science (ICIS), 2012 IEEE/ACIS 11th International Conference on
Conference_Location
Shanghai
Print_ISBN
978-1-4673-1536-4
Type
conf
DOI
10.1109/ICIS.2012.17
Filename
6211102
Link To Document