@Article{2018.100000061,
AUTHOR = {Shu Gao, Zhen Wang, Liangchen Chen},
TITLE = {SI Bitmap Index and Optimization for Membership Query},
JOURNAL = {Intelligent Automation \& Soft Computing},
VOLUME = {25},
YEAR = {2019},
NUMBER = {4},
PAGES = {683--689},
URL = {http://www.techscience.com/iasc/v25n4/40330},
ISSN = {2326-005X},
ABSTRACT = {The explosive growth of data produced by internet of things has contributed to 
the abundance of data. Since then, efficient indexing and querying techniques 
for data retrieval has become a major challenge. Bitmap index and its extension 
techniques, which involve a bit sequence that represents a specified property and 
indicates the data items that satisfies this property, are well-known methods to 
improve processing time for complex and interactive queries on the read-mostly 
or append-only data. This paper proposes an improved bitmap index technique, 
named Sliced-Interval Bitmap Index (SI Bitmap Index), which is efficient in both 
space and response time for Membership query. It also describes the method to 
optimize Membership query, based on SI Bitmap Index, in four steps. 
Experimental results indicate that SI Bitmap Index is space-saving as well as high 
efficiency on Membership query.},
DOI = {10.31209/2018.100000061}
}