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» Probabilistic Ranking Queries on Gaussians
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VLDB
2007
ACM
129views Database» more  VLDB 2007»
13 years 12 months ago
Anytime Measures for Top-k Algorithms
Top-k queries on large multi-attribute data sets are fundamental operations in information retrieval and ranking applications. In this paper, we initiate research on the anytime b...
Benjamin Arai, Gautam Das, Dimitrios Gunopulos, Ni...
WWW
2008
ACM
14 years 6 months ago
Mining the search trails of surfing crowds: identifying relevant websites from user activity
The paper proposes identifying relevant information sources from the history of combined searching and browsing behavior of many Web users. While it has been previously shown that...
Mikhail Bilenko, Ryen W. White
SIGIR
2011
ACM
12 years 8 months ago
Cluster-based fusion of retrieved lists
Methods for fusing document lists that were retrieved in response to a query often use retrieval scores (or ranks) of documents in the lists. We present a novel probabilistic fusi...
Anna Khudyak Kozorovitzky, Oren Kurland
WWW
2007
ACM
14 years 6 months ago
Extraction and search of chemical formulae in text documents on the web
Often scientists seek to search for articles on the Web related to a particular chemical. When a scientist searches for a chemical formula using a search engine today, she gets ar...
Bingjun Sun, Qingzhao Tan, Prasenjit Mitra, C. Lee...
VLDB
2009
ACM
159views Database» more  VLDB 2009»
14 years 6 months ago
Anytime measures for top-k algorithms on exact and fuzzy data sets
Top-k queries on large multi-attribute data sets are fundamental operations in information retrieval and ranking applications. In this article, we initiate research on the anytime ...
Benjamin Arai, Gautam Das, Dimitrios Gunopulos, Ni...