Modeling the relationships between the users DB and the web-log file of a large virtual community

2003 ◽  
Vol 36 (16) ◽  
pp. 211-216
Author(s):  
Sergio M. Savaresi ◽  
Simone Garatti ◽  
Sergio Bittanti
Keyword(s):  
Virtual Community ◽  
Web Log ◽  
Log File ◽  
The Web

scholarly journals Application of Data Mining on Web Usage Data for Security: WebSecuDMiner

2019 ◽  
Author(s):  
Muhammad Zia Aftab Khan ◽  
Jihyun Park
Keyword(s):  
Design Methodology ◽  
Access Pattern ◽  
User Research ◽  
Web Log ◽  
Web Access ◽  
User Access ◽  
Log File ◽  
Access Patterns ◽  
Web Access Pattern ◽  
The Web

The purpose of this paper is to develop WebSecuDMiner algorithm to discover unusual web access patterns based on analysing the potential rules hidden in web server log and user navigation history. Design/methodology/approach: WebSecuDMiner uses equivalence class transformation (ECLAT) algorithm to extract user access patterns from the web log data, which will be used to identify the user access behaviours pattern and detect unusual one. Data extracted from the web serve log and user browsing behaviour is exploited to retrieve the web access pattern that is produced by the same user. Findings: WebSecuDMiner is used to detect whether any unauthorized access have been posed and take appropriate decisions regarding the review of the original rights of suspicious user. Research limitations/implications: The present work uses the database which is extracted from web serve log file and user browsing behaviour. Although the page is viewed by the user, the visit is not recorded in the server log file, since it can be access from the browser's cache.

A Constraint Programming Approach for Web Log Mining

2016 ◽  
Vol 11 (4) ◽  
pp. 24-42 ◽  
Author(s):  
Amina Kemmar ◽  
Yahia Lebbah ◽  
Samir Loudni
Keyword(s):  
Constraint Programming ◽  
Pattern Mining ◽  
Programming Approach ◽  
Web Log Mining ◽  
Web Log ◽  
Web Access ◽  
Log Mining ◽  
Log File ◽  
Access Patterns ◽  
The Web

Mining web access patterns consists in extracting knowledge from server log files. This problem is represented as a sequential pattern mining problem (SPM) which allows to extract patterns which are sequences of accesses that occur frequently in the web log file. There are in the literature many efficient algorithms to solve SMP (e.g., GSP, SPADE, PrefixSpan, WAP-tree, LAPIN, PLWAP). Despite the effectiveness of these methods, they do not allow to express and to handle new constraints defined on patterns, new implementations are required. Recently, many approaches based on constraint programming (CP) was proposed to solve SPM in a declarative and generic way. Since no CP-based approach was applied for mining web access patterns, the authors introduce in this paper an efficient CP-based approach for solving the web log mining problem. They bring back the problem of web log mining to SPM within a CP environment which enables to handle various constraints. Experimental results on non-trivial web log mining problems show the effectiveness of the authors' CP-based mining approach.

scholarly journals The Role of Data Preprocessing System on Web Log Files for Mining Students Access Logs

2020 ◽  
Vol 9 (1) ◽  
pp. 1045-1050
Keyword(s):  
Data Storage ◽  
Web Mining ◽  
Web Log ◽  
Log Files ◽  
Significant Stage ◽  
Log File ◽  
Access Logs ◽  
The Web ◽  
The Ideal

Nowadays, WWW has grown into significant and vast data storage. Every one of clients' exercises will be put away in log record. The log file shows the eagerness on the website. With an abundant use of web, the log file size is developing hurriedly. Web mining is a utilization of information digging innovations for immense information storehouses. It is the procedure of uncover data from web information. Before applying web mining procedures, the information in the web log must be pre-processed, consolidated and changed. It is essential for the web excavators to use smart apparatuses so as to discover, concentrate, channel and assess the ideal data. The information preprocessing stage is the most significant stage during the time spent web mining and is basic and complex in fruitful extraction of helpful information. The web logs are circulated in nature also they are non-versatile and unfeasible. Subsequently we require a broad learning calculation so as to get the ideal data.

A Web Backtracking Technique for Fraud Detection in Financial Applications

2018 ◽  
pp. 861-878
Author(s):  
Tasawar Hussain ◽  
Sohail Asghar
Keyword(s):  
Risk Mitigation ◽  
Fraud Detection ◽  
Business Rules ◽  
Security Measures ◽  
Web Based ◽  
Financial Applications ◽  
Web Log ◽  
Log File ◽  
The University ◽  
The Web

The web based applications are maturing and gaining the confidence of their users gradually, however, www still lacks the mechanism to stop the hackers. The implementing the adhesive security measures such as intrusion deduction systems and firewalls, are no more useful breaker for online frauds. The Web Backtracking Technique (WBT) is proposed for fraud detection in online financial applications by applying the hierarchical sessionization technique on the web log file. The web log Hierarchical Sessionization enhances the focused groups of users from web log and paves the path for in-depth visualization for knowledge discovery. User clicks are compared with user profiles for change in previous user click records. Those transactions which do not conform to business rules are stopped from business activities. The WBT analyzes suspicious behavior and will produce reports for security and risk mitigation purposes Furthermore, suspicious transactions are mined for the up-gradation of business rules from hierarchical sessionization. The proposed WBT is validated against the university web log data.

A Web Backtracking Technique for Fraud Detection in Financial Applications

2015 ◽  
pp. 289-307
Author(s):  
Tasawar Hussain ◽  
Sohail Asghar
Keyword(s):  
Risk Mitigation ◽  
Fraud Detection ◽  
Business Rules ◽  
Security Measures ◽  
Web Based ◽  
Financial Applications ◽  
Web Log ◽  
Log File ◽  
The University ◽  
The Web

The web based applications are maturing and gaining the confidence of their users gradually, however, www still lacks the mechanism to stop the hackers. The implementing the adhesive security measures such as intrusion deduction systems and firewalls, are no more useful breaker for online frauds. The Web Backtracking Technique (WBT) is proposed for fraud detection in online financial applications by applying the hierarchical sessionization technique on the web log file. The web log Hierarchical Sessionization enhances the focused groups of users from web log and paves the path for in-depth visualization for knowledge discovery. User clicks are compared with user profiles for change in previous user click records. Those transactions which do not conform to business rules are stopped from business activities. The WBT analyzes suspicious behavior and will produce reports for security and risk mitigation purposes Furthermore, suspicious transactions are mined for the up-gradation of business rules from hierarchical sessionization. The proposed WBT is validated against the university web log data.

scholarly journals ANALISIS WEB USAGE MINING MENGGUNAKAN METODE MODIFIED GUSTAFSON – KESSEL CLUSTERING DAN ASSOCIATION RULE PADA WEBSITE UNIVERSITAS DIPONEGORO

2020 ◽  
Vol 9 (4) ◽  
pp. 486-494
Author(s):  
Galuh Nurvinda Kurniawati ◽  
Rukun Santoso ◽  
Sugito Sugito
Keyword(s):  
Association Rule ◽  
Web Usage Mining ◽  
Engineering Faculty ◽  
Web Log ◽  
Web Usage ◽  
Log File ◽  
The Web

The comprehension of web visitors patterns are needed to develop website in an optimal fashion. The visitor pattern contained in the web log file of Diponegoro University’s website is clustered by Modified Gustafson-Kessel method. In general, this method produces two until six clusters. Two kinds of results are outlined in this paper. The first is the result contains two clusters, and the second is containing three clusters. In the first result, the visitors are divided into information seekers of student capacity and Engineering Faculty. In the second result, the visitors are divided into information seekers of Medicine Faculty, student admission and Engineering Faculty.  

Review of Improvement of Web Search Based on Web Log File

2012 ◽  
Vol 3 (2) ◽  
pp. 298-300 ◽  
Author(s):  
Soniya P. Chaudhari ◽  
Prof. Hitesh Gupta ◽  
S. J. Patil
Keyword(s):  
Neural Network ◽  
Fuzzy Logic ◽  
Web Search ◽  
Pattern Mining ◽  
Efficiency Improvement ◽  
Web Searching ◽  
Important Method ◽  
Web Log ◽  
Journal Paper ◽  
Log File

In this paper we review various research of journal paper as Web Searching efficiency improvement. Some important method based on sequential pattern Mining. Some are based on supervised learning or unsupervised learning. And also used for other method such as Fuzzy logic and neural network

The Research of the Accessibility Website Design Based on Web Log Mining

2012 ◽  
Vol 241-244 ◽  
pp. 2779-2782
Author(s):  
Heng Yao Tang ◽  
Xiao Yan Zhan
Keyword(s):  
Website Design ◽  
Web Log Mining ◽  
Web Page ◽  
Web Log ◽  
User Interests ◽  
Mining Technique ◽  
Dynamic Web ◽  
Log Mining ◽  
The Web

On the problems existing in the realization of current accessibility website, we design a web designing architecture, using the web log mining technique to extract user interests and access priority sequence and adopting the dynamic web page information to fill the web page commonly used structure, realize the intelligent , personalized accessibility.

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