DocumentCode :
3585444
Title :
Inverted Index Compression Using Multi-codes
Author :
Decai Sun ; Xiaoxia Wang
Author_Institution :
Coll. of Inf. Sci. & Technol., Bohai Univ., Jinzhou, China
Volume :
2
fYear :
2014
Firstpage :
96
Lastpage :
99
Abstract :
How to decrease the space consumed by index is a key issue in big data processing. In this paper, a new compression method is proposed to decrease the space consumption of inverted index. First, a lot of redundant integers are removed by using the techniques of splitting inverted list, adding tags and making groups. Second, the total number of small integers is increased by using d-gaps in each group. Third, these sub sequences are compressed using different codes. At last, all compressed sub sequences are combined into a long sequence. Experiment results show that our method decreases the compression ratio and its decoding speed is also fast.
Keywords :
Big Data; data compression; encoding; information retrieval; big data processing; compression ratio; d-gaps; data compression method; decoding speed; inverted index compression; multicodes; redundant integers; space consumption; Big data; Conferences; Decoding; Encoding; Indexes; Information retrieval; big data; index compression; integer coding; inverted index; text retrieval;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Design (ISCID), 2014 Seventh International Symposium on
Print_ISBN :
978-1-4799-7004-9
Type :
conf
DOI :
10.1109/ISCID.2014.81
Filename :
7081946
Link To Document :
بازگشت