A Semantic Crawler Based on an Extended CBR Algorithm

Authors:
Hai Dong;Farookh Khadeer Hussain;Elizabeth Chang
Affiliations:
Digital Ecosystems and Business Intelligence Institute, Curtin University of Technology, Perth, Australia 6845;Digital Ecosystems and Business Intelligence Institute, Curtin University of Technology, Perth, Australia 6845;Digital Ecosystems and Business Intelligence Institute, Curtin University of Technology, Perth, Australia 6845
Venue:
OTM '08 Proceedings of the OTM Confederated International Workshops and Posters on On the Move to Meaningful Internet Systems: 2008 Workshops: ADI, AWeSoMe, COMBEK, EI2N, IWSSA, MONET, OnToContent + QSI, ORM, PerSys, RDDS, SEMELS, and SWWS
Year:
2008

Citing 0
Cited 2

A QoS-based service retrieval methodology for digital ecosystems

International Journal of Web and Grid Services
A Human-Centered Semantic Service Platform for the Digital Ecosystems Environment

World Wide Web

Quantified Score

Hi-index	0.00

Visualization

Abstract

A semantic (web) crawler refers to a series of web crawlers designed for harvesting semantic web content. This paper presents the framework of a semantic crawler that can abstract metadata from online webpages and cluster the metadata by associating them with ontological concepts. The clustering is based on a CBR algorithm which is adopted in the field of problem solving. We reveal the technical details with regard to ontological concept and metadata format, and the extended CBR algorithm. In addition, the system implementation and evaluation details are provided in detail, finalized by our conclusion and further works.