Data Science: Journal of Computing and Applied Informatics
Vol. 1 No. 1 (2017): Data Science: Journal of Computing and Applied Informatics (JoCAI)

Improving Data Collection on Article Clustering by Using Distributed Focused Crawler

Dani Gunawan (Universitas Sumatera Utara)
Amalia Amalia (Universitas Sumatera Utara)
Atras Najwan (Universitas Sumatera Utara)



Article Info

Publish Date
18 Jul 2017

Abstract

Collecting or harvesting data from the Internet is often done by using web crawler. General web crawler is developed to be more focus on certain topic. The type of this web crawler called focused crawler. To improve the datacollection performance, creating focused crawler is not enough as the focused crawler makes efficient usage of network bandwidth and storage capacity. This research proposes a distributed focused crawler in order to improve the web crawler performance which also efficient in network bandwidth and storage capacity. This distributed focused crawler implements crawling scheduling, site ordering to determine URL queue, and focused crawler by using Naïve Bayes. This research also tests the web crawling performance by conducting multithreaded, then observe the CPU and memory utilization. The conclusion is the web crawling performance will be decrease when too many threads are used. As the consequences, the CPU and memory utilization will be very high, meanwhile performance of the distributed focused crawler will be low.

Copyrights © 2017






Journal Info

Abbrev

JoCAI

Publisher

Subject

Computer Science & IT

Description

Data Science: Journal of Computing and Applied Informatics (JoCAI) is a peer-reviewed biannual journal (January and July) published by TALENTA Publisher and organized by Faculty of Computer Science and Information Technology, Universitas Sumatera Utara (USU) as an open access journal. It welcomes ...