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          <string-name>Figure</string-name>
        </contrib>
        <contrib contrib-type="author">
          <string-name>: Radial Tree Drawing of a Web Document</string-name>
        </contrib>
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      <pub-date>
        <year>2002</year>
      </pub-date>
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      <p>root tree, and second, the traversal of the tree by retrieving
node and nd the chapter and section edges; the second task
linearizes the webgraph and nds the next and prev edges.
the next node. The rst task helps us to nd the rst c hild
These rules will be applied until all edges are classied so
of visualization the chapter and section edges are mapped to
This function receives the root node (Start Page Node) of
The rst task is implemen ted in the function get first child.
two steps: rst, the ordering of the children nodes of the
tree edges and a radial tree drawing is applied (Figure 2).
the chapters and sections are fully resolved. For the purpose
The classication of the edges (or links) algorithm has
the subtree and returns the rst of its c hildren nodes. We
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Previous
8
12
2
17
ING RDF
4. REPORT OF LINK CLASSIFICATION US›
Figure 4: Example of the Typed Links Drawing
// section edges
mark(v);
// Linear traversal
int linear traversal(PNODE root)
return error;
g
next = get next vertex(next, &amp;error);
f
// get rst c hild of children nodes
g
g
next = get unmarked neighbor(v,error);
f
classify next prev edges(v,next);
// leaf nodes
// Linear traversal of the webgraph
next = get rst child(v, error);
// Get next node in linear traversal
if(next &amp;&amp; *error)
PNODE get next vertex(PNODE v, int *error)
classify section edges(v);
while(next &amp;&amp; error) f
// chapter edges
// next and previous edges
if(!next &amp;&amp; *error) f
int error = 0;
g
PNODE next = root;
return next;
if(next &amp;&amp; *error)
classify chapter edges(root);
PNODE next;
Our algorithm is of linear time complexity as each node
assigned a type, the chapter and section nodes are mapped
Our algorithm fails when all the counts of the table of
and its children are classied as chapter and section edges.
the current node and the not-visited neighbors are classied
ordering of the nodes of the webgraph. The edges between
to backward edges (green color). Afterwards, a tree or
rarst node. For example, Figure 5 shows a simple hierarchical
to tree edges (black color), the next edges are mapped to
foras next and prev edges. The edges between the current node
graph traversal. Once all edges of the webgraph have been
Table 3 shows the algorithm of the second step of the
webWithout that table we cannot conclude which node is the
neighbor nodes all counts are one as shown in Table 4.
ward edges (magenta color), and the prev edges are mapped
structure the webgraph. (Figures 2 and 4).
webgraph where we cannot infer what node is the rst node;
gets visited a constant number of times.
it is either node 2 or 8. When we construct the table of
dial tree drawing can be applied to visualize the hierarchical
neighbor nodes (Table 1) are one since we will not be able
to construct the table of previous and next nodes (Table 2).
of WWW 6 Conference, Santa Clara, USA, 1997.
http://www.w3.org/TR/html401/ , 1999.
[7] O. Lassila and R. Swick, W3C, Resource Description
Framework (RDF) Model and Syntax Specication.
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[8] Mapuccino http://www.ibm.com/java/mapuccino/
summaries,
July 2001.
[11] J. Punin and M. Krishnamoorthy, \WWWPal System
World Machine.
[2] T. Berners-Lee, Notation 3.
June 1999.
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[3] D. Brickley, RDF sitemaps and Dublin Core site
2000.
[5] O. De Troyer and T. Decruyenaere, \Conceptual
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April 2001.
Modelling of Web Sites for End Users," WWW
http://www.w3.org/2000/10/swap/Overview.html,
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Orlando, November, 1988.
February 2001.
[9] Y. Maarek and I. Shaul, \WebCutter: A System for
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http://wwww.w3.org/TR/REC-rdf-syntax, 1999.
http://purl.org/net/rdf/papers/sitemap/02),
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[6] N. Drakos, \From text to hypertext: A post-hoc
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