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» Capturing User Intent for Information Retrieval
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ICPR
2006
IEEE
14 years 8 months ago
Texture Image Retrieval Using Novel Non-separable Filter Banks Based on Centrally Symmetric Matrices
Though millions of images are stored in a large digital image library today, the user can not access or make full use of these image information unless the digital image library i...
Patrick Shen-Pei Wang, Xinge You, Yuan Yan Tang, Y...
MLDM
1999
Springer
13 years 11 months ago
Independent Feature Analysis for Image Retrieval
Content-based image retrieval methods based on the Euclidean metric expect the feature space to be isotropic. They su€er from unequal di€erential relevance of features in comput...
Jing Peng, Bir Bhanu
WWW
2007
ACM
14 years 8 months ago
Information flow modeling based on diffusion rate for prediction and ranking
Information flows in a network where individuals influence each other. The diffusion rate captures how efficiently the information can diffuse among the users in the network. We p...
Xiaodan Song, Yun Chi, Koji Hino, Belle L. Tseng
SIGIR
2003
ACM
14 years 23 days ago
Fractal summarization: summarization based on fractal theory
In this paper, we introduce the fractal summarization model based on the fractal theory. In fractal summarization, the important information is captured from the source text by ex...
Christopher C. Yang, Fu Lee Wang
CONTEXT
2007
Springer
14 years 1 months ago
Discovering Hidden Contextual Factors for Implicit Feedback
Abstract. This paper presents a statistical framework based on Principal Component Analysis (PCA) for discovering the contextual factors which most strongly influence user behavio...
Massimo Melucci, Ryen W. White