The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Development of a Novel Compressed Index-Query Web Search Engine Model
Abstract
In this paper, the authors present a description of a new Web search engine model, the compressed index-query (CIQ) Web search engine model. This model incorporates two bit-level compression layers implemented at the back-end processor (server) side, one layer resides after the indexer acting as a second compression layer to generate a double compressed index (index compressor), and the second layer resides after the query parser for query compression (query compressor) to enable bit-level compressed index-query search. The data compression algorithm used in this model is the Hamming codes-based data compression (HCDC) algorithm, which is an asymmetric, lossless, bit-level algorithm permits CIQ search. The different components of the new Web model are implemented in a prototype CIQ test tool (CIQTT), which is used as a test bench to validate the accuracy and integrity of the retrieved data and evaluate the performance of the proposed model. The test results demonstrate that the proposed CIQ model reduces disk space requirements and searching time by more than 24%, and attains a 100% agreement when compared with an uncompressed model.
Related Content
|
Rachna Rana, Pankaj Bhambri.
© 2025.
30 pages.
|
|
Rachna Rana, Pankaj Bhambri.
© 2025.
42 pages.
|
|
Neeta Baporikar.
© 2025.
42 pages.
|
|
Ananya Pandey, Jipson Joseph, Manshu Goyal.
© 2025.
24 pages.
|
|
Usharani Bhimavarapu.
© 2025.
16 pages.
|
|
Supriya Dam.
© 2025.
32 pages.
|
|
Nina Lestari, Nur Azizah Wahyuni, Muhammad Younus, Andi Luhur Prianto, Aqmal Reza Amri, Ahmad Harakan, Achmad Nurmandi, Hajira Gul, Ibrahim Shah, Ihyani Malik.
© 2025.
32 pages.
|
|
|