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» Feature selection for ranking using boosted trees
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PAMI
2012
13 years 2 months ago
IntentSearch: Capturing User Intention for One-Click Internet Image Search
—Web-scale image search engines (e.g. Google Image Search, Bing Image Search) mostly rely on surrounding text features. It is difficult for them to interpret users’ search int...
Xiaoou Tang, Ke Liu, Jingyu Cui, Fang Wen, Xiaogan...
JMLR
2010
206views more  JMLR 2010»
14 years 6 months ago
Learning Translation Invariant Kernels for Classification
Appropriate selection of the kernel function, which implicitly defines the feature space of an algorithm, has a crucial role in the success of kernel methods. In this paper, we co...
Sayed Kamaledin Ghiasi Shirazi, Reza Safabakhsh, M...
WWW
2002
ACM
16 years 10 days ago
Probabilistic question answering on the web
Web-based search engines such as Google and NorthernLight return documents that are relevant to a user query, not answers to user questions. We have developed an architecture that...
Dragomir R. Radev, Weiguo Fan, Hong Qi, Harris Wu,...
AAAI
2004
15 years 1 months ago
Text Classification by Labeling Words
Traditionally, text classifiers are built from labeled training examples. Labeling is usually done manually by human experts (or the users), which is a labor intensive and time co...
Bing Liu, Xiaoli Li, Wee Sun Lee, Philip S. Yu
BMCBI
2007
125views more  BMCBI 2007»
14 years 11 months ago
Identification of discriminative characteristics for clusters from biologic data with InforBIO software
Background: There are a number of different methods for generation of trees and algorithms for phylogenetic analysis in the study of bacterial taxonomy. Genotypic information, suc...
Naoto Tanaka, Masataka Uchino, Satoru Miyazaki, Hi...