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» Answering Queries using Humans, Algorithms and Databases
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MIR
2010
ACM
207views Multimedia» more  MIR 2010»
13 years 8 months 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...
WWW
2009
ACM
14 years 4 months ago
Building term suggestion relational graphs from collective intelligence
This paper proposes an effective approach to provide relevant search terms for conceptual Web search. ‘Semantic Term Suggestion’ function has been included so that users can f...
Jyh-Ren Shieh, Yung-Huan Hsieh, Yang-Ting Yeh, Tse...
KAIS
2006
110views more  KAIS 2006»
13 years 9 months ago
Multi-step density-based clustering
Abstract. Data mining in large databases of complex objects from scientific, engineering or multimedia applications is getting more and more important. In many areas, complex dista...
Stefan Brecheisen, Hans-Peter Kriegel, Martin Pfei...
ICCV
2007
IEEE
14 years 11 months ago
Learning Auto-Structured Regressor from Uncertain Nonnegative Labels
In this paper, we take the human age and pose estimation problems as examples to study automatic designing regressor from training samples with uncertain nonnegative labels. First...
Shuicheng Yan, Huan Wang, Xiaoou Tang, Thomas S. H...
VLDB
2007
ACM
155views Database» more  VLDB 2007»
14 years 10 months ago
Towards Graph Containment Search and Indexing
Given a set of model graphs D and a query graph q, containment search aims to find all model graphs g D such that q contains g (q g). Due to the wide adoption of graph models, f...
Chen Chen, Xifeng Yan, Philip S. Yu, Jiawei Han, D...