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» Learning Classifiers from Semantically Heterogeneous Data
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AAAI
2007
14 years 18 days ago
Recognizing Textual Entailment Using a Subsequence Kernel Method
We present a novel approach to recognizing Textual nt. Structural features are constructed from abstract tree descriptions, which are automatically extracted from syntactic depend...
Rui Wang 0005, Günter Neumann
ICDM
2009
IEEE
137views Data Mining» more  ICDM 2009»
14 years 5 months ago
Regression Learning Vector Quantization
— Learning Vector Quantization (LVQ) is a popular class of nearest prototype classifiers for multiclass classification. Learning algorithms from this family are widely used becau...
Mihajlo Grbovic, Slobodan Vucetic
ICRA
2010
IEEE
125views Robotics» more  ICRA 2010»
13 years 8 months ago
Inferring the semantics of direction signs in public places
Abstract— Most large-scale public environments provide direction signs to facilitate the orientation for humans and to find their way to a goal location in the environment. Thus...
Jérôme Maye, Luciano Spinello, Rudolp...
NLDB
2010
Springer
13 years 8 months ago
Extracting Meronymy Relationships from Domain-Specific, Textual Corporate Databases
Abstract. Various techniques for learning meronymy relationships from opendomain corpora exist. However, extracting meronymy relationships from domain-specific, textual corporate d...
Ashwin Ittoo, Gosse Bouma, Laura Maruster, Hans Wo...
WWW
2004
ACM
14 years 11 months ago
OntoMiner: bootstrapping ontologies from overlapping domain specific web sites
In this paper, we present automated techniques for bootstrapping and populating specialized domain ontologies by organizing and mining a set of relevant overlapping Web sites prov...
Hasan Davulcu, Srinivas Vadrevu, Saravanakumar Nag...