Generating and Adjusting Web Sub-Graph Displays for Web Navigation

2004 ◽  
pp. 241-253
Author(s):  
Wei Lai ◽  
Maolin Huang ◽  
Kang Zhang
Keyword(s):  
Web Navigation ◽  
Web Graph ◽  
Display Window ◽  
The Web ◽  
Online Web

A graph can be used for web navigation. The whole of cyberspace can be regarded as one huge graph. To explore this huge graph, it is critical to find an effective method for tracking a sequence of the graph’s subsets (web sub-graphs) based on the user’s focus. This chapter introduces our method for generating and adjusting web sub-graph displays in the process of web navigation. Any online web sub-graph should fit in the display window. To enhance the display, there should not be any overlap between node images in the web sub-graph. Our system ensures that any online web sub-graph has no overlapping node images by letting the user, or the system itself, define the visible and invisible parts of the web graph.

scholarly journals Online web navigation assistant

2021 ◽  
Vol 31 (1) ◽  
pp. 116-131
Author(s):  
N.M. Ali ◽  
A.M. Gadallah ◽  
H.A. Hefny ◽  
B.A. Novikov
Keyword(s):  
Information Overload ◽  
Specific Weight ◽  
The Internet ◽  
Fully Integrated ◽  
Web Navigation ◽  
Proposed Model ◽  
Alternative Approaches ◽  
Available Information ◽  
The Web ◽  
Online Web

The problem of finding relevant data while searching the internet represents a big challenge for web users due to the enormous amounts of available information on the web. These difficulties are related to the well-known problem of information overload. In this work, we propose an online web assistant called OWNA. We developed a fully integrated framework for making recommendations in real-time based on web usage mining techniques. Our work starts with preparing raw data, then extracting useful information that helps build a knowledge base as well as assigns a specific weight for certain factors. The experiments show the advantages of the proposed model against alternative approaches.

scholarly journals Special Issue on Algorithms and Models for the Web Graph

2009 ◽  
Vol 6 (3) ◽  
pp. 255-256
Author(s):  
Konstantin Avrachenkov ◽  
Debora Donato ◽  
Nelly Litvak
Keyword(s):  
Special Issue ◽  
Web Graph ◽  
The Web

MapReduce Based Information Retrieval Algorithms for Efficient Ranking of Webpages

2013 ◽  
pp. 250-265
Author(s):  
K.G. Srinivasa ◽  
Anil Kumar Muppalla ◽  
Varun A. Bharghava ◽  
M. Amulya
Keyword(s):  
Search Engines ◽  
World Wide ◽  
Speed Of Convergence ◽  
User Choice ◽  
Link Structure ◽  
Ranking Algorithms ◽  
The World ◽  
Retrieval Algorithms ◽  
Web Graph ◽  
The Web

In this paper, the authors discuss the MapReduce implementation of crawler, indexer and ranking algorithms in search engines. The proposed algorithms are used in search engines to retrieve results from the World Wide Web. A crawler and an indexer in a MapReduce environment are used to improve the speed of crawling and indexing. The proposed ranking algorithm is an iterative method that makes use of the link structure of the Web and is developed using MapReduce framework to improve the speed of convergence of ranking the WebPages. Categorization is used to retrieve and order the results according to the user choice to personalize the search. A new score is introduced in this paper that is associated with each WebPage and is calculated using user’s query and number of occurrences of the terms in the query in the document corpus. The experiments are conducted on Web graph datasets and the results are compared with the serial versions of crawler, indexer and ranking algorithms.

Introduction

2021 ◽  
pp. 1-36
Author(s):  
Vadim Zverovich
Keyword(s):  
Graph Theory ◽  
Biological Networks ◽  
Real Life ◽  
Scale Free ◽  
Graph Theoretic ◽  
Life Problems ◽  
Scale Free Networks ◽  
Web Graph ◽  
The Web

This chapter gives a brief overview of selected applications of graph theory, many of which gave rise to the development of graph theory itself. A range of such applications extends from puzzles and games to serious scientific and real-life problems, thus illustrating the diversity of applications. The first section is devoted to the six earliest applications of graph theory. The next section introduces so-called scale-free networks, which include the web graph, social and biological networks. The last section describes a number of graph-theoretic algorithms, which can be used to tackle a number of interesting applications and problems of graph theory.

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