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ECML
2006
Springer
15 years 5 months ago
A Discriminative Approach for the Retrieval of Images from Text Queries
This work proposes a new approach to the retrieval of images from text queries. Contrasting with previous work, this method relies on a discriminative model: the parameters are sel...
David Grangier, Florent Monay, Samy Bengio
WSDM
2010
ACM
245views Data Mining» more  WSDM 2010»
15 years 11 months ago
Improving Quality of Training Data for Learning to Rank Using Click-Through Data
In information retrieval, relevance of documents with respect to queries is usually judged by humans, and used in evaluation and/or learning of ranking functions. Previous work ha...
Jingfang Xu, Chuanliang Chen, Gu Xu, Hang Li, Elbi...
MIR
2010
ACM
207views Multimedia» more  MIR 2010»
15 years 5 days ago
Learning to rank for content-based image retrieval
In Content-based Image Retrieval (CBIR), accurately ranking the returned images is of paramount importance, since users consider mostly the topmost results. The typical ranking st...
Fabio F. Faria, Adriano Veloso, Humberto Mossri de...
IR
2010
15 years 6 days ago
Learning to rank with (a lot of) word features
In this article we present Supervised Semantic Indexing (SSI) which defines a class of nonlinear (quadratic) models that are discriminatively trained to directly map from the word...
Bing Bai, Jason Weston, David Grangier, Ronan Coll...
EMNLP
2007
15 years 3 months ago
Enhancing Single-Document Summarization by Combining RankNet and Third-Party Sources
We present a new approach to automatic summarization based on neural nets, called NetSum. We extract a set of features from each sentence that helps identify its importance in the...
Krysta Marie Svore, Lucy Vanderwende, Christopher ...