Web Usage Mining through Associative Models

Author(s):  
Paolo Giudici ◽  
Paola Cerchiello

The aim of this contribution is to show how the information, concerning the order in which the pages of a Web site are visited, can be profitably used to predict the visit behaviour at the site. Usually every click corresponds to the visualization of a Web page. Thus, a Web clickstream defines the sequence of the Web pages requested by a user. Such a sequence identifies a user session.

2018 ◽  
Vol 17 (06) ◽  
pp. 1743-1776 ◽  
Author(s):  
Jozef Kapusta ◽  
Michal Munk ◽  
Martin Drlik

The different web mining methods and techniques can help to solve some typical issues of the contemporary websites, contribute to more effective personalization, improve a website structure and reorganize its web pages. However, only several papers tried to combine web structure and web usage mining (WUM) methods with this aim. The paper researches if and how the combination of selected web structure and WUM methods can identify misplaced web pages and how they can contribute to improving the website structure. The paper analyzes the relationship between the estimated importance of the web page from the web page creator’s point of view using the web structure mining method based on PageRank and visitors’ real perception of the importance of that individual web page using the WUM method based on sequence patterns analysis, which eliminates the problem with repeated visits of the same web page during one session. The results prove that the expected probability of accesses to the individual web page correlates with the observed visit rate obtained from the log files using the WUM method. Furthermore, the website can be improved based on the consequent application of the residual analysis on the obtained results. The applicability of the proposed combination of the web structure and WUM methods is presented on two case studies from different application domains of the contemporary web. As a result, the web pages, which are underestimated or overestimated by the web page creators, are successfully identified in both cases.


Author(s):  
Ahmed El Azab ◽  
Mahmood A. Mahmood ◽  
Abd El-Aziz

Web usage mining techniques and applications across industries is still exploratory and, despite an increase in academic research, there are challenge of analyze web which quantitatively capture web users' common interests and characterize their underlying tasks. This chapter addresses the problem of how to support web usage mining techniques and applications across industries by combining language of web pages and algorithms that used in web data mining. Existing research in web usage mining techniques tend to focus on finding out how each techniques can apply in different industries fields. However, there is little evidence that researchers have approached the issue of web usage mining across industries. Consequently, the aim of this chapter is to provide an overview of how the web usage mining techniques and applications across industries can be supported.


2015 ◽  
Vol 12 (1) ◽  
pp. 91-114 ◽  
Author(s):  
Víctor Prieto ◽  
Manuel Álvarez ◽  
Víctor Carneiro ◽  
Fidel Cacheda

Search engines use crawlers to traverse the Web in order to download web pages and build their indexes. Maintaining these indexes up-to-date is an essential task to ensure the quality of search results. However, changes in web pages are unpredictable. Identifying the moment when a web page changes as soon as possible and with minimal computational cost is a major challenge. In this article we present the Web Change Detection system that, in a best case scenario, is capable to detect, almost in real time, when a web page changes. In a worst case scenario, it will require, on average, 12 minutes to detect a change on a low PageRank web site and about one minute on a web site with high PageRank. Meanwhile, current search engines require more than a day, on average, to detect a modification in a web page (in both cases).


2004 ◽  
Vol 4 (1) ◽  
Author(s):  
David Carabantes Alarcón ◽  
Carmen García Carrión ◽  
Juan Vicente Beneit Montesinos

La calidad en Internet tiene un gran valor, y más aún cuando se trata de una página web sobre salud como es un recurso sobre drogodependencias. El presente artículo recoge los estimadores y sistemas más destacados sobre calidad web para el desarrollo de un sistema específico de valoración de la calidad de recursos web sobre drogodependencias. Se ha realizado una prueba de viabilidad mediante el análisis de las principales páginas web sobre este tema (n=60), recogiendo la valoración, desde el punto de vista del usuario, de la calidad de los recursos. Se han detectado aspectos de mejora en cuanto a la exactitud y fiabilidad de la información, autoría, y desarrollo de descripciones y valoraciones de los enlaces externos. AbstractThe quality in Internet has a great value, and still more when is a web page on health like a resource of drug dependence. This paper contains the estimators and systems on quality in the web for the development of a specific system to value the quality of a web site about drug dependence. A test of viability by means of the analysis of the main web pages has been made on this subject, gathering the valuation from the point of view of the user of the quality of the resources. Aspects of improvement as the exactitude and reliability of the information, responsibility, and development of descriptions and valuations of the external links have been detected.


2018 ◽  
Vol 8 (4) ◽  
pp. 1-13
Author(s):  
Rajnikant Bhagwan Wagh ◽  
Jayantrao Bhaurao Patil

Recommendation systems are growing very rapidly. While surfing, users frequently miss the goal of their search and lost in information overload problem. To overcome this information overload problem, the authors have proposed a novel web page recommendation system to save surfing time of user. The users are analyzed when they surf through a particular web site. Authors have used relationship matrix and frequency matrix for effectively finding the connectivity among the web pages of similar users. These webpages are divided into various clusters using enhanced graph based partitioning concept. Authors classify active users more accurately to found clusters. Threshold values are used in both clustering and classification stages for more appropriate results. Experimental results show that authors get around 61% accuracy, 37% coverage and 46% F1 measure. It helps in improved surfing experience of users.


Personification of the present disclosure can be viewed as providing methods for creating a web site. In this respect, one embodiment includes the following steps: receiving a choice of a design template to be used in creating the website, the design template providing an initial layout for pages of the website and recommended content, rendering for display a representation of the website from the design template in a development environment, wherein the representation provides controls for editing content and layout of the website representation and the rendering produces HTML files that are displayed to a user and enabling the user to edit design features of the website based upon a rendered view of the website in the development environment, a presently displayed representation of a web page having editing tools embedded in the web page. Preferably, models conform to various types of web pages and other features that are typically found or visible on websites. There may be different options for each feature. The innovation is to provide a platform for making it easy to build websites and pages based on stored templates that enable the website and pages to be modified and configured without the user needing to write any software code


2013 ◽  
Vol 718-720 ◽  
pp. 2074-2079
Author(s):  
Ting Zhong Wang ◽  
Gang Long Fan

Web usage mining is the information about the user data extraction, transformation, analysis and model processing, extracted from the auxiliary business decision of key data. Intelligent site refers to the use of the Web server log for user access patterns and provide personalized service for users. The paper proposes the development and design of intelligent web site based on web usage mining. This paper presents the access interest measure method and the traditional consider only clicks visit interest measure method, recommend less deviation, has better recommendation results.


2011 ◽  
Vol 219-220 ◽  
pp. 98-102
Author(s):  
Kai Xi Xie ◽  
Ting Gui Chen

In this paper, we combine the web mining and fuzzy clustering and give the concept of web fuzzy clustering processing model and its application. We also introduce the web fuzzy direct clustering method in brief. Web fuzzy clustering can be used in the web user clustering and web page clustering of web usage mining.


2003 ◽  
Vol 13 (3) ◽  
pp. 545-548
Author(s):  
Eileen C. Herring ◽  
Richard A. Criley

The Hawaiian Native Plant Propagation Web Site (http://pdcs.ctahr.hawaii.edu:591/hawnprop) is a collection of organized propagation information for selected Hawaiian indigenous and endemic plants. It was designed to provide easy access to this information for university extension personnel, researchers, students, conservationists, and nursery and landscape professionals. Journals and newsletters published in Hawaii provided the most relevant data for this Web site. The first prototype was a database-driven Web site that provided sophisticated search capability and dynamically generated Web pages for each plant record. Subsequent testing of the prototype identified a number of usability problems. These problems were corrected by redesigning the Web site using a hybrid databasestatic Web page approach. The database software search features are retained, but each database record is linked to a static Web page containing the propagation information for a specific plant.


2018 ◽  
Vol 7 (1.7) ◽  
pp. 199
Author(s):  
Blessy Jenila R ◽  
Bharathi S

The development of trhe web has made a major test for guiding the client to the pages in their regions.Useful knowledge disclosure from web use information and acceptable learning portrayal for successful page suggestion are urgent and testing.In this paper we propose a novel technique to effectively give a better site page proposal through semantic upgrade by coordinating the space and web use learning of a site.Two new models are proposed to the learning.Semantic system is used to the web pages and the relations between the pages.Conceptional model produces a semantic system for web use information,which is the combination of learning and web use information.Various inquires have been created to inquiry about these learning base.Based on these questions ,an arrangement of suggestion methodologies have been proposed to produce fitting site page proposals to the client.The suggestion comes about have been contrasted and the outcomes got from a progressed existing Web Usage Mining(WUM)strategy.The exploratory outcomes show that the proposed technique delivers essentialy higher execution than the WUM technique.


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