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SIGMOD
2008
ACM
206views Database» more  SIGMOD 2008»
14 years 7 months ago
Ad-hoc aggregations of ranked lists in the presence of hierarchies
A variety of web sites and web based services produce textual lists at varying time granularities ranked according to several criteria. For example, Google Trends produces lists o...
Nilesh Bansal, Sudipto Guha, Nick Koudas
KDD
2006
ACM
134views Data Mining» more  KDD 2006»
14 years 8 months ago
Learning to rank networked entities
Several algorithms have been proposed to learn to rank entities modeled as feature vectors, based on relevance feedback. However, these algorithms do not model network connections...
Alekh Agarwal, Soumen Chakrabarti, Sunny Aggarwal
WIDM
2005
ACM
14 years 1 months ago
DirectoryRank: ordering pages in web directories
Web Directories are repositories of Web pages organized in a hierarchy of topics and sub-topics. In this paper, we present DirectoryRank, a ranking framework that orders the pages...
Vlassis Krikos, Sofia Stamou, Pavlos Kokosis, Alex...
WWW
2004
ACM
14 years 8 months ago
Distributed ranking over peer-to-peer networks
Query flooding is a problem existing in Peer-to-Peer networks like Gnutella. Firework Query Model solves this problem by Peer Clustering and routes the query message more intellig...
Dexter Chi Wai Siu, Tak Pang Lau
SIGIR
2011
ACM
12 years 10 months ago
Learning to rank from a noisy crowd
We study how to best use crowdsourced relevance judgments learning to rank [1, 7]. We integrate two lines of prior work: unreliable crowd-based binary annotation for binary classi...
Abhimanu Kumar, Matthew Lease