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KDD
2006
ACM
134views Data Mining» more  KDD 2006»
14 years 9 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
ACSC
2007
IEEE
14 years 3 months ago
Exploring Human Judgement of Digital Imagery
Statistical learning methods are commonly applied in content-based video and image retrieval. Such methods require a large number of examples which are usually obtained through a ...
Timo Volkmer, James A. Thom, Seyed M. M. Tahaghogh...
ECIR
2010
Springer
13 years 10 months ago
Learning to Select a Ranking Function
Abstract. Learning To Rank (LTR) techniques aim to learn an effective document ranking function by combining several document features. While the function learned may be uniformly ...
Jie Peng, Craig Macdonald, Iadh Ounis
PERCOM
2005
ACM
14 years 8 months ago
PICASSO: Pervasive Information Chronicling, Access, Search, and Sharing for Organizations
Several researchers have pointed out and begun to demonstrate that it is now possible to digitize an entire lifetime of experiences into a pocket-sized storage device, and thus to...
Gopal Pingali, Mark Podlaseck, Sinem Güven
SIGIR
2012
ACM
11 years 11 months ago
Evaluating aggregated search pages
Aggregating search results from a variety of heterogeneous sources or verticals such as news, image and video into a single interface is a popular paradigm in web search. Although...
Ke Zhou, Ronan Cummins, Mounia Lalmas, Joemon M. J...