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KDD
2012
ACM
205views Data Mining» more  KDD 2012»
13 years 6 months ago
Rank-loss support instance machines for MIML instance annotation
Multi-instance multi-label learning (MIML) is a framework for supervised classification where the objects to be classified are bags of instances associated with multiple labels....
Forrest Briggs, Xiaoli Z. Fern, Raviv Raich
ICPR
2008
IEEE
16 years 5 months ago
Multiple kernel learning from sets of partially matching image features
Abstract: Kernel classifiers based on Support Vector Machines (SVM) have achieved state-ofthe-art results in several visual classification tasks, however, recent publications and d...
Guo ShengYang, Min Tan, Si-Yao Fu, Zeng-Guang Hou,...
ACMICEC
2006
ACM
141views ECommerce» more  ACMICEC 2006»
15 years 10 months ago
From HTML documents to web tables and rules
We present a browser-extending Semantic Web extraction system that maps HTML documents to tables and, where possible, to rules. First, the basic data extractor ViPER distills and ...
Kai Simon, Georg Lausen, Harold Boley
SIGIR
2008
ACM
15 years 3 months ago
Learning to rank with partially-labeled data
Ranking algorithms, whose goal is to appropriately order a set of objects/documents, are an important component of information retrieval systems. Previous work on ranking algorith...
Kevin Duh, Katrin Kirchhoff
AIRS
2005
Springer
15 years 9 months ago
Query Expansion with the Minimum Relevance Judgments
Query expansion techniques generally select new query terms from a set of top ranked documents. Although a user’s manual judgment of those documents would much help to select goo...
Masayuki Okabe, Kyoji Umemura, Seiji Yamada