Application of ARIMA(1,1,0) Model for Predicting Time Delay of Search Engine Crawlers

Jeeva Jose () and P. Sojan Lal ()

Informatica Economica, 2013, vol. 17, issue 4, 26-38

Abstract: World Wide Web is growing at a tremendous rate in terms of the number of visitors and number of web pages. Search engine crawlers are highly automated programs that periodically visit the web and index web pages. The behavior of search engines could be used in analyzing server load, quality of search engines, dynamics of search engine crawlers, ethics of search engines etc. The more the number of visits of a crawler to a web site, the more it contributes to the workload. The time delay between two consecutive visits of a crawler determines the dynamicity of the crawlers. The ARIMA(1,1,0) Model in time series analysis works well with the forecasting of the time delay between the visits of search crawlers at web sites. We considered 5 search engine crawlers, all of which could be modeled using ARIMA(1,1,0).The results of this study is useful in analyzing the server load.

Keywords: ARIMA; Search Engine Crawler; Web logs; Time delay; Prediction (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (1)

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