Welcome to the InfoSci Platform
Reference Hub2
Comparing Different Sparse Matrix Storage Structures as Index Structure for Arabic Text Collection

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

Basel Bani-Ismail, Ghassan Kanaan
Copyright: © 2012 |Volume: 2 |Issue: 2 |Pages: 16
ISSN: 2155-6377|EISSN: 2155-6385|EISBN13: 9781466612624|DOI: 10.4018/ijirr.2012040105
Cite Article Cite Article

MLA

Bani-Ismail, Basel, and Ghassan Kanaan. "Comparing Different Sparse Matrix Storage Structures as Index Structure for Arabic Text Collection." IJIRR vol.2, no.2 2012: pp.52-67. http://doi.org/10.4018/ijirr.2012040105

APA

Bani-Ismail, B. & Kanaan, G. (2012). Comparing Different Sparse Matrix Storage Structures as Index Structure for Arabic Text Collection. International Journal of Information Retrieval Research (IJIRR), 2(2), 52-67. http://doi.org/10.4018/ijirr.2012040105

Chicago

Bani-Ismail, Basel, and Ghassan Kanaan. "Comparing Different Sparse Matrix Storage Structures as Index Structure for Arabic Text Collection," International Journal of Information Retrieval Research (IJIRR) 2, no.2: 52-67. http://doi.org/10.4018/ijirr.2012040105

Export Reference

Mendeley
Favorite Full-Issue Download

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).

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.