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» On Kernel Methods for Relational Learning
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APWEB
2010
Springer
15 years 3 months ago
Multi-View Clustering with Web and Linguistic Features for Relation Extraction
Binary semantic relation extraction is particularly useful for various NLP and Web applications. Currently Webbased methods and Linguistic-based methods are two types of leading me...
Yulan Yan, Haibo Li, Yutaka Matsuo, Zhenglu Yang, ...
WEBI
2010
Springer
15 years 1 months ago
Relations Expansion: Extracting Relationship Instances from the Web
In this paper, we propose a Relation Expansion framework, which uses a few seed sentences marked up with two entities to expand a set of sentences containing target relations. Duri...
Haibo Li, Yutaka Matsuo, Mitsuru Ishizuka
GLOBECOM
2008
IEEE
15 years 9 months ago
Distributed Regression in Sensor Networks with a Reduced-Order Kernel Model
Abstract—Over the past few years, wireless sensor networks received tremendous attention for monitoring physical phenomena, such as the temperature field in a given region. Appl...
Paul Honeine, Mehdi Essoloh, Cédric Richard...
ICML
2001
IEEE
16 years 4 months ago
Learning Probabilistic Models of Relational Structure
Most real-world data is stored in relational form. In contrast, most statistical learning methods work with "flat" data representations, forcing us to convert our data i...
Lise Getoor, Nir Friedman, Daphne Koller, Benjamin...
GIS
2010
ACM
15 years 1 months ago
Kernelized map matching
Map matching is a fundamental operation in many applications such as traffic analysis and location-aware services, the killer apps for ubiquitous computing. In the past, several m...
Ahmed Jawad, Kristian Kersting