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ESWA
2008
127views more  ESWA 2008»
15 years 6 months ago
A two-level relevance feedback mechanism for image retrieval
Content-based image retrieval (CBIR) is a group of techniques that analyzes the visual features (such as color, shape, texture) of an example image or image subregion to find simi...
Pei-Cheng Cheng, Been-Chian Chien, Hao-Ren Ke, Wei...
RECSYS
2010
ACM
15 years 4 months ago
List-wise learning to rank with matrix factorization for collaborative filtering
A ranking approach, ListRank-MF, is proposed for collaborative filtering that combines a list-wise learning-to-rank algorithm with matrix factorization (MF). A ranked list of item...
Yue Shi, Martha Larson, Alan Hanjalic
EJASMP
2010
112views more  EJASMP 2010»
15 years 1 months ago
Query-Driven Strategy for On-the-Fly Term Spotting in Spontaneous Speech
Spoken utterance retrieval was largely studied in the last decades, with the purpose of indexing large audio databases or of detecting keywords in continuous speech streams. While...
Mickael Rouvier, Georges Linares, Benjamin Lecoute...
ICCV
2011
IEEE
14 years 6 months ago
HEAT: Iterative Relevance Feedback with One Million Images
It has been shown repeatedly that iterative relevance feedback is a very efficient solution for content-based image retrieval. However, no existing system scales gracefully to hu...
Nicolae Suditu, Francois Fleuret
SIGIR
2005
ACM
16 years 4 days ago
Question answering passage retrieval using dependency relations
State-of-the-art question answering (QA) systems employ termdensity ranking to retrieve answer passages. Such methods often retrieve incorrect passages as relationships among ques...
Hang Cui, Renxu Sun, Keya Li, Min-Yen Kan, Tat-Sen...