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 :
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