A Study on Prediction of User Behavior Based on Web Server Log Files in Web Usage Mining

2017 ◽  
Author(s):  
Anurag Kumar ◽  
◽  
Vaishali Ahirwar ◽  
Ravi Kumar Singh ◽  
◽  
...  
Keyword(s):  
User Behavior ◽  
Web Server ◽  
Web Usage Mining ◽  
Web Usage ◽  
Log Files ◽  
Behavior Based

They Know What You Will Do Next Click

2020 ◽  
pp. 100-122
Author(s):  
Serra Çelik
Keyword(s):  
Focus Group ◽  
User Behavior ◽  
Web Usage Mining ◽  
Web Log ◽  
Web Usage ◽  
User Behaviors ◽  
Log Files ◽  
The Web

This chapter focuses on predicting web user behaviors. When web users enter a website, every move they make on that website is stored as web log files. Unlike the focus group or questionnaire, the log files reflect real user behavior. It can easily be said that having actual user behavior is a gold value for the organizations. In this chapter, the ways of extracting user patterns (user behavior) from the log files are sought. In this context, the web usage mining process is explained. Some web usage mining techniques are mentioned.

scholarly journals Automated User Behavior Mapping Using Web Usage Mining

2020 ◽  
Vol 6 (12) ◽  
pp. 257-261
Author(s):  
IJMTST061248
Keyword(s):  
Real Time ◽  
User Behavior ◽  
Web Usage Mining ◽  
Time Behavior ◽  
End User ◽  
Web Page ◽  
The Real ◽  
Web Log ◽  
Web Usage ◽  
Log Files

Automated User Behavior Mapping is an application of web usage mining using which we can see the real-time behavior of end user visiting a particular web page automatically. The technologies used in this are socket programming for real-time communication between the server and the user accessing the website for collection of web log data and selenium web driver for automating the user behavior using web log files.

scholarly journals User Identification in the Process of Web Usage Data Preprocessing

2019 ◽  
Vol 14 (09) ◽  
pp. 21 ◽  
Author(s):  
Jozef Kapusta ◽  
Michal Munk ◽  
Dominik Halvoník ◽  
Martin Drlík
Keyword(s):  
User Behavior ◽  
Web Server ◽  
Web Browser ◽  
Ip Address ◽  
User Session ◽  
Log Files ◽  
The Us ◽  
Log File ◽  
Default Form

If we are talking about user behavior analytics, we have to understand what the main source of valuable information is. One of these sources is definitely a web server. There are multiple places where we can extract the necessary data. The most common ways are to search for these data in access log, error log, custom log files of web server, proxy server log file, web browser log, browser cookies etc. A web server log is in its default form known as a Common Log File (W3C, 1995) and keeps information about IP address; date and time of visit; ac-cessed and referenced resource. There are standardized methodologies which contain several steps leading to extract new knowledge from provided data. Usu-ally, the first step is in each one of them to identify users, users’ sessions, page views, and clickstreams. This process is called pre-processing. Main goal of this stage is to receive unprocessed web server log file as input and after processing outputs meaningful representations which can be used in next phase. In this pa-per, we describe in detail user session identification which can be considered as most important part of data pre-processing. Our paper aims to compare the us-er/session identification using the STT with the identification of user/session us-ing cookies. This comparison was performed concerning the quality of the se-quential rules generated, i.e., a comparison was made regarding generation useful, trivial and inexplicable rules.

Web Usage Mining Issues in Big Data

2021 ◽  
pp. 102-112
Author(s):  
Sunny Sharma ◽  
Manisha Malhotra
Keyword(s):  
Data Mining ◽  
Big Data ◽  
User Behavior ◽  
Web Usage Mining ◽  
Web Personalization ◽  
Data Mining Techniques ◽  
Meaningful Information ◽  
Web Usage ◽  
Use Of Data ◽  
The Web

Web usage mining is the use of data mining techniques to analyze user behavior in order to better serve the needs of the user. This process of personalization uses a set of techniques and methods for discovering the linking structure of information on the web. The goal of web personalization is to improve the user experience by mining the meaningful information and presented the retrieved information in a way the user intends. The arrival of big data instigated novel issues to the personalization community. This chapter provides an overview of personalization, big data, and identifies challenges related to web personalization with respect to big data. It also presents some approaches and models to fill the gap between big data and web personalization. Further, this research brings additional opportunities to web personalization from the perspective of big data.

Extracting Knowledge from Web Data

2014 ◽  
Vol 7 (4) ◽  
pp. 27-41
Author(s):  
Hanane Ezzikouri ◽  
Mohamed Fakir ◽  
Cherki Daoui ◽  
Mohamed Erritali
Keyword(s):  
Web Mining ◽  
User Behavior ◽  
Data Extraction ◽  
Research Area ◽  
Web Usage Mining ◽  
Web Data ◽  
Main Research ◽  
Web Log ◽  
Web Usage ◽  
Log File

The user behavior on a website triggers a sequence of queries that have a result which is the display of certain pages. The Information about these queries (including the names of the resources requested and responses from the Web server) are stored in a text file called a log file. Analysis of server log file can provide significant and useful information. Web Mining is the extraction of interesting and potentially useful patterns and implicit information from artifacts or activity related to the World Wide Web. Web usage mining is a main research area in Web mining focused on learning about Web users and their interactions with Web sites. The motive of mining is to find users' access models automatically and quickly from the vast Web log file, such as frequent access paths, frequent access page groups and user clustering. Through Web Usage Mining, several information left by user access can be mined which will provide foundation for decision making of organizations, Also the process of Web mining was defined as the set of techniques designed to explore, process and analyze large masses of consecutive information activities on the Internet, has three main steps: data preprocessing, extraction of reasons of the use and the interpretation of results. This paper will start with the presentation of different formats of web log files, then it will present the different preprocessing method that have been used, and finally it presents a system for “Web content and Usage Mining'' for web data extraction and web site analysis using Data Mining Algorithms Apriori, FPGrowth, K-Means, KNN, and ID3.

Web Usage Minning using Patterns with Different Algorithm

2017 ◽  
pp. 1-9
Author(s):  
Keyword(s):  
Data Mining ◽  
Web Usage Mining ◽  
Data Discovery ◽  
Web Log ◽  
Data Usage ◽  
Web Usage ◽  
Log Files ◽  
Content Mining ◽  
User Data ◽  
Data Content

Web usage mining is a part of data mining. Data usage mining is divided into three parts 1) Data content mining 2) Data structured mining 3) Data usage mining. In this paper I am discussing about log files which are used in data usage mining. Log files are used to store user’s activity in web server using websites. So that websites can be improved by gathering user data. Web usage mining having three sub parts which is reprocessing, data discovery and data analysis. Further, in this paper, details about web log files are discussed. Three algorithms are discussed which are used for patterns of log files. There comparison is showed in this paper with the help of graphs.

A User Behavior-Based Agent for Improving Web Usage

2002 ◽  
pp. 1168-1185 ◽  
Author(s):  
Francesco Buccafurri ◽  
Gianluca Lax ◽  
Domenico Rosaci ◽  
Domenico Ursino
Keyword(s):  
User Behavior ◽  
Web Usage ◽  
Behavior Based
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