Welcome to the InfoSci Platform
Reference Hub29
A Fireworks Algorithm for Modern Web Information Retrieval with Visual Results Mining

A Fireworks Algorithm for Modern Web Information Retrieval with Visual Results Mining

Hadj Ahmed Bouarara, Reda Mohamed Hamou, Abdelmalek Amine, Amine Rahmani
Copyright: © 2015 |Volume: 6 |Issue: 3 |Pages: 23
ISSN: 1947-9263|EISSN: 1947-9271|EISBN13: 9781466678293|DOI: 10.4018/IJSIR.2015070101
Cite Article Cite Article

MLA

Bouarara, Hadj Ahmed, et al. "A Fireworks Algorithm for Modern Web Information Retrieval with Visual Results Mining." IJSIR vol.6, no.3 2015: pp.1-23. http://doi.org/10.4018/IJSIR.2015070101

APA

Bouarara, H. A., Hamou, R. M., Amine, A., & Rahmani, A. (2015). A Fireworks Algorithm for Modern Web Information Retrieval with Visual Results Mining. International Journal of Swarm Intelligence Research (IJSIR), 6(3), 1-23. http://doi.org/10.4018/IJSIR.2015070101

Chicago

Bouarara, Hadj Ahmed, et al. "A Fireworks Algorithm for Modern Web Information Retrieval with Visual Results Mining," International Journal of Swarm Intelligence Research (IJSIR) 6, no.3: 1-23. http://doi.org/10.4018/IJSIR.2015070101

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

The popularization of computers, the number of electronic documents available online /offline and the explosion of electronic communication have deeply rocked the relationship between man and information. Nowadays, we are awash in a rising tide of information where the web has impacted on almost every aspect of our life. Merely, the development of automatic tools for an efficient access to this huge amount of digital information appears as a necessity. This paper deals on the unveiling of a new web information retrieval system using fireworks algorithm (FWA-IR). It is based on a random explosion of fireworks and a set of operators (displacement, mapping, mutation, and selection). Each explosion of firework is a potential solution for the need of user (query). It generates a set of sparks (documents) with two locations (relevant and irrelevant). The authors experiments were performed on the MEDLARS dataset and using the validation measures (recall, precision, f-measure, silence, noise and accuracy) by studying the sensitive parameters of this technique (initial location number, iteration number, mutation probability, fitness function, selection method, text representation, and distance measure), aimed to show the benefit derived from using such approach compared to the results of others methods existed in literature (taboo search, simulated annealing, and naïve method). Finally, a result-mining tool was achieved for the purpose to see the outcome in graphical form (3d cub and cobweb) with more realism using the functionalities of zooming and rotation.

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.