The network structure of a hyperlinked environment can be a rich source of information about the content of the environment, provided we have effective means for understanding it. We develop a set of algorithmic tools for extracting information from the link structures of such environments

of hyperlinked documents. The essence of our approach is to augment a previous connectivity analysis based algorithm with content analysis. We identify three problems with the existing approach and devise algorithms to tackle them. The results of a user evaluation are reported that show an improvement

a surge of research activity in the area of web mining using link analysis algorithms. Subsequent to the first generation of algorithms, a significant amount of improvements and variations appeared. However, the issue of stability has received little attention in spite of its practical and theoretical implications. For instance, the issue of “link spamming ” is closely related to stability: is it possible to boost up the rank of a page by adding/removing few nodes to/from it? In this paper, we study the stability aspect of various link analysis algorithms concluding that some algorithms are more robust than others. Also, we show that those unstable algorithms may become stable when they are properly “randomized”.

This article addresses a problem with the existing approach by Clever Algorithm on studies of Web hyperlink structure: It does not take into consideration of user behavior when following multiple consecutive hyperlinks. We present an improved algorithm and show that any connected hyperlink graph

A typical learning method using the Internet is exploratory learning, where learners construct knowledge through exploring the web autonomously.

Because diverse users each modify the link structure of the WWW within a relatively small scope (by creating web-pages on their own sites that link to other web-pages), the global stucture of the WWW is unpredictable and must be analyzed a posteriori. To make effective use of the wealth of information that the WWW provides, we need a way of extracting meaningful information with respect to a global search query that we make. We focus on broad-topic queries, i.e., “Tell me about automobile manufacturers. ” A naive search strategy might be to return any page containing the phrase “automobile manufacturers”. Unfortunately, there are literally hundreds of thousands of webpages meeting this criteria, far too many for a person to look through alone. Furthermore, the websites of major automobile manufacturers are unlikely to even contain the phrase “automobile manufacturers”. So simply returning the pages with the most occurrences of the query string will obviously not suffice (we call these pages the “text-based results”). Moreover, we maintain that any real measure of the quality of a search result is inherently subjective, as it and has much to do with the context and desires of the individual making the query. We want to identify the authoritative, informative web pages for a particular query. In the above example, the Toyota home page and important reviews might be considered authorities,

Abstract To examine the emergent properties of information seeking in hyperlinked environments, in this paper we developed a cyclic model. Using this model as a framework, the relationships among perceived goal difficulty, goal success, and self-efficacy were examined. Selfefficacy

Here, we investigate the graph structure of the Web-graph, the directed graph whose nodes are static pages and edges are links between these pages. Broder et al. [1] looked at some basic properties of this graph. They found that the web-graph has one large weakly connected component consisting of 91 % of pages. This is not surprising since there is only one world wide web. This fact remains intact even when all nodes of degree more than 5 are removed: there still is a large component with more than 59 million pages. This shows that there are many different paths between pairs of nodes and the web will not be partitioned even if certain important pages were removed. The web was found to contain one strongly connected component (SCC) of approximately 56 million pages that were mutually reachable. Figure 1: Connectivity of the web Figure 1 gives an overview of the structure. One can pass from any node of IN through SCC to any node of OUT. Hanging off IN and OUT are TENDRILS containing nodes that are reachable from portions of IN, or that can reach portions of OUT, without passage through SCC. It is possible for a TENDRIL hanging off from IN to be hooked into a TENDRIL leading into OUT, forming a TUBE – a passage from a portion of IN to a portion of OUT without touching SCC. They found that apart from the roughly 59 million pages in

HotJava is a World-Wide Web browser that adds dynamic behavior to hypertext access by supporting the downloading and execution of architecture-neutral, interactive applets from inside a Web page. HotJava is written in Java, a new object-oriented language and environment developed at Sun

In [13] we describe an architecture for building special-purpose agents for solving the information capture and access problem in large, multi-media data environments with uncertainty in data representation and interpretation. The key idea is to recognize the underlying structure that exists