TY - GEN
T1 - Detection of Web subsites
T2 - IEEE/WIC/ACM International Conference on Web Intelligence, WI 2007
AU - Rodrigues, Eduarda Mendes
AU - Milic-Frayling, Natasa
AU - Fortuna, Blaz
PY - 2007
Y1 - 2007
N2 - Web sites are often organized into several regions, each dedicated to a specific topic or serving a particular function. From a user's perspective, these regions typically form coherent sets of pages characterized by a distinct navigation structure and page layout - we refer to them as subsites. In this paper we propose to characterize Web site structure as a collection of subsites and devise a method for detecting subsites and entry points for subsite navigation. In our approach we use a new model for representing Web site structure called Link Structure Graph (LSG). The LSG captures a complete hyperlink structure of a Web site and models link associations reflected in the page layout. We analyze a sample of Web sites and compare the LSG based approach to commonly used statistics for Web graph analysis. We demonstrate that LSG approach reveals site properties that are beyond the reach of standard site models. Furthermore, we devise a method for evaluating the performance of subsite detection algorithms and provide evaluation guidelines.
AB - Web sites are often organized into several regions, each dedicated to a specific topic or serving a particular function. From a user's perspective, these regions typically form coherent sets of pages characterized by a distinct navigation structure and page layout - we refer to them as subsites. In this paper we propose to characterize Web site structure as a collection of subsites and devise a method for detecting subsites and entry points for subsite navigation. In our approach we use a new model for representing Web site structure called Link Structure Graph (LSG). The LSG captures a complete hyperlink structure of a Web site and models link associations reflected in the page layout. We analyze a sample of Web sites and compare the LSG based approach to commonly used statistics for Web graph analysis. We demonstrate that LSG approach reveals site properties that are beyond the reach of standard site models. Furthermore, we devise a method for evaluating the performance of subsite detection algorithms and provide evaluation guidelines.
UR - http://www.scopus.com/inward/record.url?scp=48349139492&partnerID=8YFLogxK
U2 - 10.1109/WI.2007.44
DO - 10.1109/WI.2007.44
M3 - Conference contribution
AN - SCOPUS:48349139492
SN - 0769530265
SN - 9780769530260
T3 - Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence, WI 2007
SP - 66
EP - 76
BT - Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence, WI 2007
Y2 - 2 November 2007 through 5 November 2007
ER -