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  4. An efficient data transformation technique for web log
 
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An efficient data transformation technique for web log

Journal
Lecture Notes in Engineering and Computer Science
Date Issued
2017
Author(s)
Madihah Mohd Saudi 
Universiti Sains Islam Malaysia 
Ridzuan F.
Hashim H.A.-B.
Abstract
Growth of data over time especially in term of volume, velocity, value, veracity and variety led to many challenges especially in extracting useful information from it. Furthermore, managing and transforming raw data into a readable format is crucial for subsequent analysis. Therefore, this paper presents a new web server log file classification and an efficient way of transforming raw web log files by using knowledge database discovery (KDD) technique into a readable format for data mining analysis. An experiment was conducted to the raw web log files, in a controlled lab environment, by using KDD technique and k-nearest neighbor (IBk) algorithm. Based on the experiment conducted, the IBk algorithm generates 99.66% for true positive rate (TPR) and 0.34% for false positive rate (FPR) which indicates the significant efficiency of the new web log file classification and data transformation technique used in this paper.
Subjects

Big Data

Data transformation

Knowledge database di...

Log analysis

Big data

Blogs

Classification (of in...

Metadata

Nearest neighbor sear...

Data transformation

False positive rates

K-nearest neighbors

Knowledge database

Log analysis

True positive rates

Web log file

Web server logs

Data mining

File(s)
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An Efficient Data Transformation Technique for Web Log.pdf

Size

1.11 MB

Format

Adobe PDF

Checksum

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