Columbia Academic Commons (Columbia University) · 2000 · 225 citations · 15 references
Many web resources are relevant primarily to limited geographical communities, such as local restaurant or apartment sites, while others, like national newspapers, serve broader audiences, yet current search engines largely ignore this geographic scope. The paper introduces techniques to automatically compute the geographical scope of web resources. These techniques analyze the textual content of resources and the geographic distribution of hyperlinks pointing to them. An extensive evaluation on real web data demonstrates the effectiveness of the strategies, and a geographically‑aware search engine was built to showcase them.
Many information resources on the web are relevant primarily to limited geographical communities. For instance, web sites containing information on restaurants, theaters, and apartment rentals are relevant primarily to web users in geographical proximity to these locations. In contrast, other information resources are relevant to a broader geographical community. For instance, an on-line newspaper may be relevant to users across the United States. Unfortunately, current web search engines largely ignore the geographical scope of web resources. In this paper, we introduce techniques for automatically computing the geographical scope of web resources, based on the textual content of the resources, as well as on the geographical distribution of hyperlinks to them. We report an extensive experimental evaluation of our strategies using real web data. Finally, we describe a geographicallyaware search engine that we have built to showcase our techniques.
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Authoritative sources in a hyperlinked environment
Jon Kleinberg · Journal of the ACM · 1999 · 9K citations · Full text
Inferring Web communities from link topology
David Gibson, Jon Kleinberg, Prabhakar Raghavan · 1998 · 772 citations