NDLI: Knowledge discovery in web traffic log: A case study of facebook usage in kasetsart university

Content Provider	IEEE Xplore Digital Library
Author	Tantithamthavorn, C. Rungsawang, A.
Copyright Year	2012
Description	Author affiliation: Massive Information and Knowledge Engineering Laboratory (MIKE Lab), Department of Computer Engineering, Faculty of Engineering, Kasetsart University. Bangkok, Thailand (Tantithamthavorn, C.; Rungsawang, A.)
Abstract	Recognizing and understanding knowledge flow between user interactions in social networks are valuable for sociology, economy, political science, and marketing. In this paper, we present a methodology in order to extract information and discover knowledge from a web traffic log. Our study is based on traffic and login history logs of Kasetsart University's network during a 7-days period from March 1–7, 2011. The summarized HTTP sessions show 39,046 distinct users together with 25,894 IP addresses. We conduct a pattern analysis in six aspects: The Origin of HTTP Requests, Distribution of HTTP Requests at the level of hostname, Time spent communicating online, Overall Traffic Workload Analysis, Facebook Traffic Workload Analysis and Web Access Patterns. The results reveal many interesting patterns and knowledge from raw data.
Starting Page	247
Ending Page	252
File Size	1170816
Page Count	6
File Format	PDF
ISBN	9781467319201
e-ISBN	9781467319218
DOI	10.1109/JCSSE.2012.6261960
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-05-30
Publisher Place	Thailand
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computers Educational institutions Internet IP networks Servers Facebook
Content Type	Text
Resource Type	Article

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