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» Interactive Object-Based Retrieval Using Relevance Feedback
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CONTEXT
2007
Springer
14 years 2 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
AMR
2007
Springer
171views Multimedia» more  AMR 2007»
14 years 2 months ago
Automatic Image Annotation with Relevance Feedback and Latent Semantic Analysis
The goal of this paper is to study the image-concept relationship as it pertains to image annotation. We demonstrate how automatic annotation of images can be implemented on partia...
Donn Morrison, Stéphane Marchand-Maillet, E...
CHI
2011
ACM
12 years 11 months ago
Apolo: making sense of large network data by combining rich user interaction and machine learning
Extracting useful knowledge from large network datasets has become a fundamental challenge in many domains, from scientific literature to social networks and the web. We introduc...
Duen Horng Chau, Aniket Kittur, Jason I. Hong, Chr...
ICMCS
2006
IEEE
153views Multimedia» more  ICMCS 2006»
14 years 2 months ago
Learning-Based Interactive Video Retrieval System
This paper presents an interactive video event retrieval system based on improved adaboost learning. This system consists of three main steps. Firstly, a long video sequence is pa...
Chi-Jiunn Wu, Hui-Chi Zeng, Szu-Hao Huang, Shang-H...
COLING
2010
13 years 2 months ago
Negative Feedback: The Forsaken Nature Available for Re-ranking
Re-ranking for Information Retrieval aims to elevate relevant feedbacks and depress negative ones in initial retrieval result list. Compared to relevance feedback-based re-ranking...
Yu Hong, Qing-qing Cai, Song Hua, Jian-Min Yao, Qi...