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.

A DYNAMICS RECOMMENDATION SYSTEM BASED ON LOG MINING

2002 ◽  
Vol 13 (04) ◽  
pp. 521-530 ◽  
Author(s):  
WEN GAO ◽  
SHI WANG ◽  
BIN LIU
Keyword(s):  
Recommendation System ◽  
Predictive Accuracy ◽  
Web Pages ◽  
Web Log Mining ◽  
Web Page ◽  
Time Dynamic ◽  
Active User ◽  
Dynamic Web ◽  
Log Mining ◽  
A Current

This paper presents a new real-time, dynamic web page recommendation system based on web-log mining. The visit sequences of previous visitors are used to train a classifier for web page recommendation. The recommendation engine identifies a current active user, and submits its visit sequence as an input to the classifier. The output of the recommendation engine is a set of recommended web pages, whose links are attached to bottom of the requested page. Our experiments show that the proposed approach is effective: the predictive accuracy is quite high (over 90%), and the time for the recommendation is quite small.

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 Recommender System for Multiple Databases Based on Web Log Mining

2021 ◽  
Vol 5 (5) ◽  
pp. 187-193
Author(s):  
Wan Hussain Wan Ishak ◽  
Nurul Farhana Ismail
Keyword(s):  
Recommender System ◽  
Information Overload ◽  
Web Log Mining ◽  
Large Collection ◽  
Information Searching ◽  
Web Log ◽  
Online Databases ◽  
Innovative Solutions ◽  
Log Mining ◽  
The Web

Finding information from a large collection of resources is a tedious and time-consuming process. Due to information overload, searchers often need help and assistance to search and find the information. Recommender system is one of the innovative solutions to the problem related to information searching and retrieval. It helps and assist searchers by recommending the possible solution based on the previous search activities. These activities can be obtained from the web log, which requires a web log mining approach to extract all the keywords. In this study, keywords obtained from the library web log were analysed and the search keyword patterns were obtained. These keyword patterns were from several databases or resources that were subscribed by the library. The finding revealed some of the popular keywords and the most searchable databases among the searchers. This information was used to design and develop the recommender system that can be used to assist other searchers. The usability test of the recommender system showed that it is beneficial and useful to the searchers. These findings will also benefit the management in planning and managing the subscription of online databases at the university’s library.

scholarly journals Verification of the fulfilment of the purposes of Basel II, Pillar 3 through application of the web log mining methods

2012 ◽  
Vol 60 (2) ◽  
pp. 217-222 ◽  
Author(s):  
M. Munk ◽  
A. Pilková ◽  
Martin Drlík ◽  
J. Kapusta ◽  
P. Švec
Keyword(s):  
Commercial Bank ◽  
Basel Ii ◽  
Application Domain ◽  
Mandatory Disclosure ◽  
Web Log Mining ◽  
Data Preparation ◽  
Web Log ◽  
Mining Methods ◽  
Log Mining ◽  
The Web

The objective of the paper is the verification of the fulfilment of the purposes of Basel II, Pillar 3 – market discipline during the recent financial crisis. The objective of the paper is to describe the current state of the working out of the project that is focused on the analysis of the market participants’ interest in mandatory disclosure of financial information by a commercial bank by means of advanced methods of web log mining. The output of the realized project will be the verification of the assumptions related to the purposes of Basel III by means of the web mining methods, the recommendations for possible reduction of mandatory disclosure of information under Basel II and III, the proposal of the methodology for data preparation for web log mining in this application domain and the generalised procedure for users’ behaviour modelling dependent on time. The schedule of the project has been divided into three phases. The paper deals with its first phase that is focusing on the data pre-processing, analysis and evaluation of the required information under Basel II, Pillar 3 since 2008 and its disclosure into the web site of a commercial bank. The authors introduce the methodologies for data preparation and known heuristic methods for path completion into web log files with respect to the particularity of investigated application domain. They propose scientific methods for modelling users’ behaviour of the webpages related to Pillar 3 with respect to time.

Web Log Mining als Controllinginstrument für Online-Shops

Controlling ◽  
2001 ◽  
Vol 13 (3) ◽  
pp. 157-166 ◽  
Author(s):  
Reinhold Mayer ◽  
Frank Bensberg ◽  
Anita Hukemann
Keyword(s):  
Web Log Mining ◽  
Web Log ◽  
Log Mining ◽  
Online Shops
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