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Search effectiveness with a breadth-first crawl
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Annual ACM Conference on Research and Development in Information Retrieval archive
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval table of contents
Singapore, Singapore
POSTER SESSION: Posters group 2: blog, tagging, opinion analysis and web IR table of contents
Pages 755-756  
Year of Publication: 2008
ISBN:978-1-60558-164-4
Authors
Dennis Fetterly  Microsoft Research, Mountain View, CA, USA
Nick Craswell  Microsoft Research, Cambridge, United Kngdm
Vishwa Vinay  Microsoft Research, Cambridge, United Kngdm
Sponsors
ACM: Association for Computing Machinery
SIGIR: ACM Special Interest Group on Information Retrieval
Publisher
ACM  New York, NY, USA
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ABSTRACT

Previous scalability experiments found that early precision improves as collection size increases. However, that was under the assumption that a collection's documents are all sampled with uniform probability from the same population. We contrast this to a large breadth-first web crawl, an important scenario in real-world Web search, where the early documents have quite different characteristics from the later documents.



Collaborative Colleagues:
Dennis Fetterly: colleagues
Nick Craswell: colleagues
Vishwa Vinay: colleagues