Chapter 6

An Efficient Approach for Weblog Analysis using Machine Learning Techniques

Brijesh Bakariya

Abstract

Information on the internet is rapidly growing day by day. Some of the information may be related to the person or not. The amount of data on the internet is very vast, and it is tough to store and manage. So the organization of massive amounts of data has also produced a problem in data accessing. The rapid expansion of the web has provided an excellent opportunity to analyze web access logs. Data mining techniques were applied for extracting relevant information from a massive collection of data, but now it is a traditional technique. The web data is either unstructured or semi-structured. So there is not any direct method in data mining for it. Here Python programming language and Machine Learning (ML) approach is used from handling such types of data. In this paper, we are analyzing weblog data through python. This approach is useful for time and space point of view because because python has many libraries for data analysis.

Total Pages: 89-98 (10)

Purchase Chapter  Book Details

RELATED BOOKS

.Boundary Element Methods for Heat Transfer with Phase Change Problems: Theory and Application.
.An Introduction to Sobolev Spaces.
.Exterior Calculus: Theory and Cases.
.Trefftz and Fundamental Solution-Based Finite Element Methods.