An Improved Web Page Recommendation Technique for Better Surfing Experience

2018 ◽  
Vol 8 (4) ◽  
pp. 1-13
Author(s):  
Rajnikant Bhagwan Wagh ◽  
Jayantrao Bhaurao Patil
Keyword(s):  
Web Site ◽  
Recommendation System ◽  
Information Overload ◽  
Experimental Results ◽  
Relationship Matrix ◽  
Web Pages ◽  
Threshold Values ◽  
Web Page ◽  
Clustering And Classification ◽  
The Web

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.

Web Usage Mining through Associative Models

2011 ◽  
pp. 1231-1234 ◽  
Author(s):  
Paolo Giudici ◽  
Paola Cerchiello
Keyword(s):  
Web Site ◽  
Web Usage Mining ◽  
Web Pages ◽  
Web Page ◽  
User Session ◽  
Web Usage ◽  
Associative Models ◽  
The Web

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.

Extracting Top-k Company Acquisition Relations From the Web

2017 ◽  
Vol 13 (4) ◽  
pp. 27-41 ◽  
Author(s):  
Jie Zhao ◽  
Jianfei Wang ◽  
Jia Yang ◽  
Peiquan Jin
Keyword(s):  
Rapid Development ◽  
Relation Extraction ◽  
Experimental Results ◽  
Competitive Intelligence ◽  
Web Pages ◽  
Web Content ◽  
Web Page ◽  
Competitive Strategies ◽  
The Web ◽  
Novel Algorithm

Company acquisition relation reflects a company's development intent and competitive strategies, which is an important type of enterprise competitive intelligence. In the traditional environment, the acquisition of competitive intelligence mainly relies on newspapers, internal reports, and so on, but the rapid development of the Web introduces a new way to extract company acquisition relation. In this paper, the authors study the problem of extracting company acquisition relation from huge amounts of Web pages, and propose a novel algorithm for company acquisition relation extraction. The authors' algorithm considers the tense feature of Web content and classification technology of semantic strength when extracting company acquisition relation from Web pages. It first determines the tense of each sentence in a Web page, which is then applied in sentences classification so as to evaluate the semantic strength of the candidate sentences in describing company acquisition relation. After that, the authors rank the candidate acquisition relations and return the top-k company acquisition relation. They run experiments on 6144 pages crawled through Google, and measure the performance of their algorithm under different metrics. The experimental results show that the algorithm is effective in determining the tense of sentences as well as the company acquisition relation.

scholarly journals Distributed and collaborative Web Change Detection system

2015 ◽  
Vol 12 (1) ◽  
pp. 91-114 ◽  
Author(s):  
Víctor Prieto ◽  
Manuel Álvarez ◽  
Víctor Carneiro ◽  
Fidel Cacheda
Keyword(s):  
Change Detection ◽  
Search Engines ◽  
Web Site ◽  
Detection System ◽  
Computational Cost ◽  
Web Pages ◽  
Web Page ◽  
Case Scenario ◽  
Worst Case ◽  
The Web

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).

BUILDING A KNOWLEDGE BASE FOR IMPLEMENTING A WEB-BASED COMPUTERIZED RECOMMENDATION SYSTEM

2007 ◽  
Vol 16 (05) ◽  
pp. 793-828 ◽  
Author(s):  
JUAN D. VELÁSQUEZ ◽  
VASILE PALADE
Keyword(s):  
Knowledge Base ◽  
Web Site ◽  
Web Mining ◽  
Recommendation System ◽  
The Internet ◽  
Web Pages ◽  
Web Based ◽  
Web Logs ◽  
Mining Tools ◽  
The Web

Understanding the web user browsing behaviour in order to adapt a web site to the needs of a particular user represents a key issue for many commercial companies that do their business over the Internet. This paper presents the implementation of a Knowledge Base (KB) for building web-based computerized recommender systems. The Knowledge Base consists of a Pattern Repository that contains patterns extracted from web logs and web pages, by applying various web mining tools, and a Rule Repository containing rules that describe the use of discovered patterns for building navigation or web site modification recommendations. The paper also focuses on testing the effectiveness of the proposed online and offline recommendations. An ample real-world experiment is carried out on a web site of a bank.

scholarly journals Webpage Recommendation System Based on the Social Media Semantic Details of the Website

2021 ◽  
Vol 12 (6) ◽  
pp. 237-243
Author(s):  
Dr. R.Rooba Et.al
Keyword(s):  
Recommendation System ◽  
Semantic Information ◽  
Markov Chain Model ◽  
Similarity Score ◽  
Web Pages ◽  
Chain Model ◽  
Web Page ◽  
The Social ◽  
Recommendation Accuracy ◽  
The Web

The web page recommendation is generated by using the navigational history from web server log files. Semantic Variable Length Markov Chain Model (SVLMC) is a web page recommendation system used to generate recommendation by combining a higher order Markov model with rich semantic data. The problem of state space complexity and time complexity in SVLMC was resolved by Semantic Variable Length confidence pruned Markov Chain Model (SVLCPMC) and Support vector machine based SVLCPMC (SSVLCPMC) meth-ods respectively. The recommendation accuracy was further improved by quickest change detection using Kullback-Leibler Divergence method. In this paper, socio semantic information is included with the similarity score which improves the recommendation accuracy. The social information from the social websites such as twitter is considered for web page recommendation. Initially number of web pages is collected and the similari-ty between web pages is computed by comparing their semantic information. The term frequency and inverse document frequency (tf-idf) is used to produce a composite weight, the most important terms in the web pages are extracted. Then the Pointwise Mutual Information (PMI) between the most important terms and the terms in the twitter dataset are calculated. The PMI metric measures the closeness between the twitter terms and the most important terms in the web pages. Then this measure is added with the similarity score matrix to provide the socio semantic search information for recommendation generation. The experimental results show that the pro-posed method has better performance in terms of prediction accuracy, precision, F1 measure, R measure and coverage.

Valuation and analysis of drug addiction web sites / Criterios de valoración y análisis de sitios web sobre drogodependencias

2004 ◽  
Vol 4 (1) ◽  
Author(s):  
David Carabantes Alarcón ◽  
Carmen García Carrión ◽  
Juan Vicente Beneit Montesinos
Keyword(s):  
Drug Addiction ◽  
Web Sites ◽  
Drug Dependence ◽  
Web Site ◽  
Point Of View ◽  
Web Pages ◽  
Web Page ◽  
Specific System ◽  
The Web

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.

A Qualitative Approach for Representation of Templates and Portfolios with User Accessible Environment

2021 ◽  
Vol 10 (3) ◽  
pp. 1589-1598
Keyword(s):  
Web Site ◽  
Qualitative Approach ◽  
Web Pages ◽  
Web Page ◽  
Design Features ◽  
Development Environment ◽  
Software Code ◽  
The Web ◽  
Initial Layout

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

Web Mining to Identify People of Similar Background

2010 ◽  
pp. 369-385
Author(s):  
Quanzhi Li ◽  
Yi-fang Brook Wu
Keyword(s):  
Web Site ◽  
Web Mining ◽  
Experimental Results ◽  
Web Pages ◽  
Major Research ◽  
Research Issues ◽  
New Approach ◽  
Representation Method ◽  
Textual Content ◽  
The Web

This chapter presents a new approach of mining the Web to identify people of similar background. To find similar people from the Web for a given person, two major research issues are person representation and matching persons. In this chapter, a person representation method which uses a person’s personal Web site to represent this person’s background is proposed. Based on this person representation method, the main proposed algorithm integrates textual content and hyperlink information of all the Web pages belonging to a personal Web site to represent a person and match persons. Other algorithms are also explored and compared to the main proposed algorithm. The evaluation methods and experimental results are presented.

Web Page Recommendation System Using Laplace Correction Dependent Probability and Chronological Dragonfly-Based Clustering

2018 ◽  
Vol 7 (3.27) ◽  
pp. 290
Author(s):  
Jyoti Narayan Jadhav ◽  
B Arunkumar
Keyword(s):  
Recommendation System ◽  
Pattern Mining ◽  
Web Pages ◽  
Web Page ◽  
Dragonfly Algorithm ◽  
History Of ◽  
Search History ◽  
Dependent Probability ◽  
F Measure ◽  
The Web

The web page recommenders predict and recommend the web pages to the users based on the behavior of their search history. The web page recommender system analyzes the semantics of the navigation by the user and predicts the related web pages for the user. Various recommender systems have been developed in the literature for the web page recommendation. In the first work, a web page recommendation system was developed using weighted sequential pattern mining and Wu and Li Index Fuzzy clustering (WLI-FC) algorithm. In this work, the Chronological based Dragonfly Algorithm (Chronological-DA) is proposed for recommending the webpage to the users. The proposed Chronological-DA algorithm includes the concept of the chronological for recommending the webpage based on the history of pages visited by the users. Also, the proposed recommendation system uses the concept of Laplacian correction for defining the recommendation probability. Simulation of the proposed webpage recommendation system with the chronological-DA uses the standard CTI and the MSNBC database for the experimentation, and the experimental results prove that the proposed scheme has better values of 1, 0.964, and 0.973 for precision, recall, and F-measure respectively.  

scholarly journals The Hawaiian Native Plant Propagation Web Site: Developing a Webbased Information Resource

2003 ◽  
Vol 13 (3) ◽  
pp. 545-548
Author(s):  
Eileen C. Herring ◽  
Richard A. Criley
Keyword(s):  
Web Site ◽  
Easy Access ◽  
Web Pages ◽  
Endemic Plants ◽  
Native Plant ◽  
Web Page ◽  
Plant Propagation ◽  
Usability Problems ◽  
Search Capability ◽  
The Web

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.

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