<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Saliha Mezzoudj</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A parallel content-based image retrieval system using spark and tachyon frameworks</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of King Saud University - Computer and Information Sciences</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2021</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.sciencedirect.com/science/article/pii/S1319157818307146</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">33</style></volume><pages><style face="normal" font="default" size="100%">141-149</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p style=&quot;text-align: justify;&quot;&gt;
	With the huge increase of large-scale multimedia over Internet, especially images, building Content-Based Image Retrieval (CBIR) systems for large-scale images has become a big challenge. One of the drawbacks associated with CBIR is the very long execution time. In this article, we propose a fast Content-Based Image Retrieval system using Spark (CBIR-S) targeting large-scale images. Our system is composed of two steps.&amp;nbsp;&lt;em&gt;(i) image indexation step&lt;/em&gt;, in which we use&amp;nbsp;&lt;a href=&quot;https://www.sciencedirect.com/topics/computer-science/mapreduce&quot; title=&quot;Learn more about MapReduce from ScienceDirect's AI-generated Topic Pages&quot;&gt;MapReduce&lt;/a&gt;&amp;nbsp;distributed model on Spark in order to speed up the indexation process. We also use a memory-centric&amp;nbsp;&lt;a href=&quot;https://www.sciencedirect.com/topics/computer-science/distributed-storage-system&quot; title=&quot;Learn more about distributed storage system from ScienceDirect's AI-generated Topic Pages&quot;&gt;distributed storage system&lt;/a&gt;, called Tachyon, to enhance the write operation&amp;nbsp;&lt;em&gt;(ii) image retrieving step&lt;/em&gt;&amp;nbsp;which we speed up by using a parallel k-Nearest Neighbors (k-NN) search method based on&amp;nbsp;&lt;a href=&quot;https://www.sciencedirect.com/topics/computer-science/mapreduce-model&quot; title=&quot;Learn more about MapReduce model from ScienceDirect's AI-generated Topic Pages&quot;&gt;MapReduce model&lt;/a&gt;&amp;nbsp;implemented under&amp;nbsp;&lt;a href=&quot;https://www.sciencedirect.com/topics/computer-science/apache-spark&quot; title=&quot;Learn more about Apache Spark from ScienceDirect's AI-generated Topic Pages&quot;&gt;Apache Spark&lt;/a&gt;, in addition to exploiting the cache method of spark framework. We have showed, through a wide set of experiments, the effectiveness of our approach in terms of processing time.
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