A process of knowledge discovery from web log data: Systematization and critical review
Z. Pabarskaite, and A. Raudys. Journal of Intelligent Information Systems, 28 (1):
79--104(February 2007)
Abstract
Abstract This paper presents a comprehensive survey of web log/usage mining based on over 100 research papers. This is the first survey
dedicated exclusively to web log/usage mining. The paper identifies several web log mining sub-topics including specific onessuch as data cleaning, user and session identification. Each sub-topic is explained, weaknesses and strong points are discussedand possible solutions are presented. The paper describes examples of web log mining and lists some major web log mining softwarepackages.
%0 Journal Article
%1 keyhere
%A Pabarskaite, Zidrina
%A Raudys, Aistis
%D 2007
%J Journal of Intelligent Information Systems
%K clickstream datamining
%N 1
%P 79--104
%T A process of knowledge discovery from web log data: Systematization and critical review
%U http://dx.doi.org/10.1007/s10844-006-0004-1
%V 28
%X Abstract This paper presents a comprehensive survey of web log/usage mining based on over 100 research papers. This is the first survey
dedicated exclusively to web log/usage mining. The paper identifies several web log mining sub-topics including specific onessuch as data cleaning, user and session identification. Each sub-topic is explained, weaknesses and strong points are discussedand possible solutions are presented. The paper describes examples of web log mining and lists some major web log mining softwarepackages.
@article{keyhere,
abstract = {Abstract This paper presents a comprehensive survey of web log/usage mining based on over 100 research papers. This is the first survey
dedicated exclusively to web log/usage mining. The paper identifies several web log mining sub-topics including specific onessuch as data cleaning, user and session identification. Each sub-topic is explained, weaknesses and strong points are discussedand possible solutions are presented. The paper describes examples of web log mining and lists some major web log mining softwarepackages.},
added-at = {2007-12-06T05:05:10.000+0100},
author = {Pabarskaite, Zidrina and Raudys, Aistis},
biburl = {https://www.bibsonomy.org/bibtex/27909aa09203aa901f5e33a528b347aa6/jhammerb},
description = {SpringerLink - Journal Article},
interhash = {c3d1e7be725e13d0dba18513e4259230},
intrahash = {7909aa09203aa901f5e33a528b347aa6},
journal = {Journal of Intelligent Information Systems},
keywords = {clickstream datamining},
month = {#feb#},
number = 1,
pages = {79--104},
timestamp = {2007-12-06T05:05:10.000+0100},
title = {A process of knowledge discovery from web log data: Systematization and critical review},
url = {http://dx.doi.org/10.1007/s10844-006-0004-1},
volume = 28,
year = 2007
}