Discovering gis sources on the web using summaries

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Discovering gis sources on the web using summaries

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International Conference on Digital Libraries archive
Proceedings of the 8th ACM/IEEE-CS joint conference on Digital libraries table of contents

Pittsburgh PA, PA, USA

SESSION: Geography and trust on the web table of contents

Pages 94-103

Year of Publication: 2008

ISBN:978-1-59593-998-2

Authors

Ramaswamy Hariharan	University of California, Irvine, Irvine, CA, USA
Bijit Hore	University of California, Irvine, Irvine, CA, USA
Sharad Mehrotra	University of California, Irvine, Irvine, CA, USA

Sponsors

SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web
SIGIR: ACM Special Interest Group on Information Retrieval
ACM: Association for Computing Machinery

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ACM New York, NY, USA

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ABSTRACT

In this paper, we consider the problem of discovering GIS data sources on the web. Source discovery queries for GIS data are specified using keywords and a region of interest. A source is considered relevant if it contains data that matches the keywords in the specified region. Existing techniques simply rely on textual metadata accompanying such datasets to compute relevance to user-queries. Such approaches result in poor search results, often missing the most relevant sources on the web. We address this problem by developing more meaningful summaries of GIS datasets that preserve the spatial distribution of keywords. We conduct experiments showing the effectiveness of proposed summarization techniques by significantly improving the quality of query results over baseline approaches, while guaranteeing scalability and high performance.

REFERENCES

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