23 research outputs found
Identifying Aggregates in Hypertext Structures
Hypertext systems are being used in many applications because of their
flexible structure and the great browsing freedom they give to diverse
communities of users. However, this same freedom and flexibility is the
cause of one of its main problem: the lost in hyperspace problem. One
reason for the complexity of hypertext databases is the large
number of nodes and links that compose them. To simplify this structure
we propose that nodes and links be clustered forming more abstract
structures. An abstraction is the concealment of all but relevant
properties from an object or concept.
One type of abstraction is called an aggregate. An aggregate is a set
of distinct concepts that taken together form a more abstract concept.
For example, two legs, a trunk, two arms and a head can be aggregate
together in a single higher level object called a body. In this
paper we will study the hypertext structure, i.e., the way nodes are
linked to each other in order to find aggregates in hypertext
databases. Two graph theoretical algorithms will be
used: biconnected components and strongly connected components.
(Also cross-referenced as CAR-TR-550
Curvature of Co-Links Uncovers Hidden Thematic Layers in the World Wide Web
Beyond the information stored in pages of the World Wide Web, novel types of
``meta-information'' are created when they connect to each other. This
information is a collective effect of independent users writing and linking
pages, hidden from the casual user. Accessing it and understanding the
inter-relation of connectivity and content in the WWW is a challenging problem.
We demonstrate here how thematic relationships can be located precisely by
looking only at the graph of hyperlinks, gleaning content and context from the
Web without having to read what is in the pages. We begin by noting that
reciprocal links (co-links) between pages signal a mutual recognition of
authors, and then focus on triangles containing such links, since triangles
indicate a transitive relation. The importance of triangles is quantified by
the clustering coefficient (Watts) which we interpret as a curvature
(Gromov,Bridson-Haefliger). This defines a Web-landscape whose connected
regions of high curvature characterize a common topic. We show experimentally
that reciprocity and curvature, when combined, accurately capture this
meta-information for a wide variety of topics. As an example of future
directions we analyze the neural network of C. elegans (White, Wood), using the
same methods.Comment: 8 pages, 5 figures, expanded version of earlier submission with more
example
Design of an Interface for Page Rank Calculation using Web Link Attributes Information
This paper deals with the Web Structure Mining and the different Structure Mining Algorithms like Page Rank, HITS, Trust Rank and Sel-HITS. The functioning of these algorithms are discussed. An incremental algorithm for calculation of PageRank using an interface has been formulated. This algorithm makes use of Web Link Attributes Information as key parameters and has been implemented using Visibility and Position of a Link. The application of Web Structure Mining Algorithm in an Academic Search Application has been discussed. The present work can be a useful input to Web Users, Faculty, Students and Web Administrators in a University Environment.HITS, Page Rank, Sel-HITS, Structure Mining
A Web video retrieval method using hierarchical structure of Web video groups
In this paper, we propose a Web video retrieval method that uses hierarchical structure of Web video groups. Existing retrieval systems require users to input suitable queries that identify the desired contents in order to accurately retrieve Web videos; however, the proposed method enables retrieval of the desired Web videos even if users cannot input the suitable queries. Specifically, we first select representative Web videos from a target video dataset by using link relationships between Web videos obtained via metadata ârelated videosâ and heterogeneous video features. Furthermore, by using the representative Web videos, we construct a network whose nodes and edges respectively correspond to Web videos and links between these Web videos. Then Web video groups, i.e., Web video sets with similar topics are hierarchically extracted based on strongly connected components, edge betweenness and modularity. By exhibiting the obtained hierarchical structure of Web video groups, users can easily grasp the overview of many Web videos. Consequently, even if users cannot write suitable queries that identify the desired contents, it becomes feasible to accurately retrieve the desired Web videos by selecting Web video groups according to the hierarchical structure. Experimental results on actual Web videos verify the effectiveness of our method
Supporting adaptive learning in hypertext environment : a high level timed Petri net based approach
One problem for hypertext-based learning application is to control learning paths for different learning activities. This paper first introduced related concepts of hypertext learning state space and Petri net, then proposed a high level timed Petri Net based approach to provide some kinds of adaptation for learning activities. Examples were given while explaining ways to realizing adaptive instructions. Possible future directions were also discussed at the end of this paper.<br /
Matrix model for web page community
Discovering intrinsic relationships/structures among concerned web information objects such as web pages is important for effectively processing and managing web information. In this work, a set of web pages that has its own intrinsic structure is called a web page community. This paper proposes a matrix model to describe relationships among concerned web pages. Based on this model, intrinsic relationships among pages could be revealed, and in turn a web page community could be constructed. The issues that are related to this model and its applications are investigated and studied. Some applications based on this model are presented, which demonstrate the potential of this matrix model in different kinds of web page community construction and information processing. <br /
Design of an Interface for Page Rank Calculation using Web Link Attributes Information
This paper deals with the Web Structure Mining and the different Structure Mining Algorithms like Page Rank, HITS, Trust Rank and Sel-HITS. The functioning of these algorithms are discussed. An incremental algorithm for calculation of PageRank using an interface has been formulated. This algorithm makes use of Web Link Attributes Information as key parameters and has been implemented using Visibility and Position of a Link. The application of Web Structure Mining Algorithm in an Academic Search Application has been discussed. The present work can be a useful input to Web Users, Faculty, Students and Web Administrators in a University Environment
CibermetrĂa del Web: las leyes de exponenciaciĂłn
An introduction to the power laws, enunciated by Michalis Faloutsos, is made and that allows us to make a characterization of the Web through the analysis of their topology. Their most important characteristics are described and how calculate some of the values of the most interesting functions