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» Learning to rank for information retrieval (LR4IR 2008)
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CLEF
2008
Springer
15 years 8 months ago
ParaMor and Morpho Challenge 2008
ParaMor, our unsupervised morphology induction system performed well at Morpho Challenge 2008. When ParaMor's morphological analyses, which specialize at identifying inflecti...
Christian Monson, Jaime G. Carbonell, Alon Lavie, ...
IRI
2008
IEEE
16 years 15 days ago
Biological question answering with syntactic and semantic feature matching and an improved mean reciprocal ranking measurement
Specific information on biomolecular events such as protein-protein and gene-protein interactions is essential for molecular biology researchers. However, the results derived by c...
Ryan T. K. Lin, Justin Liang-Te Chiu, Hong-Jie Dai...
DEXAW
2010
IEEE
196views Database» more  DEXAW 2010»
15 years 6 months ago
Direct Optimization of Evaluation Measures in Learning to Rank Using Particle Swarm
— One of the central issues in Learning to Rank (L2R) for Information Retrieval is to develop algorithms that construct ranking models by directly optimizing evaluation measures ...
Ósscar Alejo, Juan M. Fernández-Luna...
IR
2011
15 years 1 months ago
Learning to rank for why-question answering
In this paper, we evaluate a number of machine learning techniques for the task of ranking answers to why-questions. We use TF-IDF together with a set of 36 linguistically motivate...
Suzan Verberne, Hans van Halteren, Daphne Theijsse...
MM
2004
ACM
152views Multimedia» more  MM 2004»
15 years 11 months ago
Manifold-ranking based image retrieval
In this paper, we propose a novel transductive learning framework named manifold-ranking based image retrieval (MRBIR). Given a query image, MRBIR first makes use of a manifold ra...
Jingrui He, Mingjing Li, HongJiang Zhang, Hanghang...