A Topology-driven Approach to the Design of Web Meta-Search Clustering Engines. E, D. G., W, D., L, G., & G, L. 2005.
A Topology-driven Approach to the Design of Web Meta-Search Clustering Engines [link]Paper  doi  abstract   bibtex   
The paradigm adopted by classical Web search engines to output the results of a query is often inadequate. It typically consists of a ranked list of URLs, which may be very long and difficult to browse for the interested user. Recently, a lot of attention has been devoted to the design of Web meta-search clustering engines. These systems support the user by grouping the URLs returned by a search engine into distinct semantic categories, which are organized in a hierarchy; each category is properly labeled with a sentence that reflects its topics. However, even the most effective Web meta-search engines usually end-up by presenting many ``meaningful'' categories together with a few ``inexpressive'' categories on some specific queries. In this paper we describe a novel topology-driven approach to the design of a Web meta-search clustering engine. By this approach the set of URLs is modeled as a suitable graph and the hierarchy of categories is obtained by variants of classical graph-clustering algorithms. The topology-driven approach turns out to be comparable with traditional text-based strategies for the definition of the cluster hierarchy. In addition, our approach makes it natural to use graph visualization techniques to support the user in handling inexpressive labels. Namely, categories with inexpressive labels can be visually related to more meaningful ones.
@conference{
	11391_157529,
	author = { Di Giacomo E  and  Didimo W  and  Grilli L  and  Liotta G },
	title = {A Topology-driven Approach to the Design of Web Meta-Search Clustering Engines},
	year = {2005},
	publisher = {Springer.},
	address = {BERLIN},
	volume = {3381},
	booktitle = {SOFSEM 2005: Theory and Practice of Computer Science SOFSEM 2005: Theory and Practice of Computer Science},
	abstract = {The paradigm adopted by classical Web search engines to output

the results of a query is often inadequate. It typically

consists of a ranked list of URLs, which may be very long and difficult to browse for the interested user.

Recently, a lot of attention has been devoted to the design of Web meta-search clustering engines. These systems support the user by grouping the URLs returned

by a search engine into distinct semantic categories, which are organized

in a hierarchy; each category is properly labeled with a sentence that reflects

its topics. However, even the most effective Web meta-search engines usually

end-up by presenting many ``meaningful'' categories together with a few

``inexpressive'' categories on some specific queries.

In this paper we describe a novel topology-driven approach to the design of a

Web meta-search clustering engine. By this approach the set of URLs is modeled

as a suitable graph and the hierarchy of categories is obtained by

variants of classical graph-clustering algorithms. The topology-driven approach

turns out to be comparable with traditional text-based strategies for the

definition of the cluster hierarchy. In addition, our approach makes it natural

to use graph visualization techniques to support the user in handling

inexpressive labels. Namely, categories with inexpressive labels can be

visually related to more meaningful ones.},
	keywords = {Web search engines; Web computing; information retrieval},
	url = {http://www.springerlink.com/content/f6171408k34j2842/},
	doi = {10.1007/11618058_11},	
	pages = {106--116}
}
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