Mayank Bawa Tyson Condie U. C. Berkeley Berkeley, CA...  Home/Search
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Abstract: We consider the problem of indexing high-dimensional data for answering (approximate) similarity-search queries. Similarity indexes prove to be important in a wide variety of settings: Web search engines desire fast, parallel, main-memory-based indexes for similarity search on text data; database systems desire disk-based similarity indexes for high-dimensional data, including text and images; peer-to-peer systems desire distributed similarity indexes with low communication cost. We propose an... (Update)
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BibTeX entry: (Update)
@misc{ bawa-lsh,
author = "Mayank Bawa Bawa",
title = "LSH Forest: Self-Tuning Indexes for Similarity Search",
url = "citeseer.ist.psu.edu/bawa05lsh.html" }
Citations (may not include all citations):576 Authoritative sources in a hyperlinked environment - Kleinberg - 1998
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162 Similarity indexing with ss-tree (context) - White, Jain - 1996
154 Automatic resource compilation by analyzing hyperlink struct.. - Chakrabarti, Dom et al. - 1998
147 A quantitative analysis and performance study for similarity.. - Weber, Schek et al. - 1998
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14 Scalable data acces pp system using unbalanced search tree (context) - data, systems et al. - 2002
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