Comparing Different Sparse Matrix Storage Structures as Index Structure for Arabic Text Collection

Basel Bani-Ismail and Ghassan Kanaan
Additional contact information
Basel Bani-Ismail: Department of Computer Science, Sultan Qaboos University, Muscat, Oman
Ghassan Kanaan: Department of Computer Science, Amman Arab University, Amman, Jordan

International Journal of Information Retrieval Research (IJIRR), 2012, vol. 2, issue 2, 52-67

Abstract: In the authors’ study they evaluate and compare the storage efficiency of different sparse matrix storage structures as index structure for Arabic text collection and their corresponding sparse matrix-vector multiplication algorithms to perform query processing in any Information Retrieval (IR) system. The study covers six sparse matrix storage structures including the Coordinate Storage (COO), Compressed Sparse Row (CSR), Compressed Sparse Column (CSC), Block Coordinate (BCO), Block Sparse Row (BSR), and Block Sparse Column (BSC). Evaluation depends on the storage space requirements for each storage structure and the efficiency of the query processing algorithm. The experimental results demonstrate that CSR is more efficient in terms of storage space requirements and query processing time than the other sparse matrix storage structures. The results also show that CSR requires the least amount of disk space and performs the best in terms of query processing time compared with the other point entry storage structures (COO, CSC). The results demonstrate that BSR requires the least amount of disk space and performs the best in terms of query processing time compared with the other block entry storage structures (BCO, BSC).

Date: 2012
References: Add references at CitEc
Citations:

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 018/ijirr.2012040105 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jirr00:v:2:y:2012:i:2:p:52-67

Access Statistics for this article

International Journal of Information Retrieval Research (IJIRR) is currently edited by Zhongyu Lu

More articles in International Journal of Information Retrieval Research (IJIRR) from IGI Global
Bibliographic data for series maintained by Journal Editor ().