Improving Data Collection on Article Clustering by Using Distributed Focused Crawler

Authors

  • Dani Gunawan Universitas Sumatera Utara
  • Amalia Amalia Universitas Sumatera Utara
  • Atras Najwan Universitas Sumatera Utara

DOI:

https://doi.org/10.32734/jocai.v1.i1-82

Keywords:

data collection, cpu utilization, distributed web crawler, distributed focused crawler, focused crawler, memory utilization, multithread, web crawler

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.

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Published

2017-07-18

How to Cite

Gunawan, D., Amalia, A., & Najwan, A. (2017). Improving Data Collection on Article Clustering by Using Distributed Focused Crawler. Data Science: Journal of Computing and Applied Informatics, 1(1), 1-12. https://doi.org/10.32734/jocai.v1.i1-82