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IJCNLP
2004
Springer
15 years 9 months ago
Combining Labeled and Unlabeled Data for Learning Cross-Document Structural Relationships
Multi-document discourse analysis has emerged with the potential of improving various NLP applications. Based on the newly proposed Cross-document Structure Theory (CST), this pap...
Zhu Zhang, Dragomir R. Radev
AAAI
2007
15 years 6 months ago
Relation Extraction from Wikipedia Using Subtree Mining
The exponential growth and reliability of Wikipedia have made it a promising data source for intelligent systems. The first challenge of Wikipedia is to make the encyclopedia mac...
Dat P. T. Nguyen, Yutaka Matsuo, Mitsuru Ishizuka
JMLR
2002
138views more  JMLR 2002»
15 years 3 months ago
Learning Probabilistic Models of Link Structure
Most real-world data is heterogeneous and richly interconnected. Examples include the Web, hypertext, bibliometric data and social networks. In contrast, most statistical learning...
Lise Getoor, Nir Friedman, Daphne Koller, Benjamin...
200
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CVPR
2012
IEEE
13 years 6 months ago
Structured Local Predictors for image labelling
In this paper we introduce Structured Local Predictors (SLP) – A new formulation that considers the image labelling problem from a structured learning point of view. SLP are loc...
Samuel Rota Bulò, Peter Kontschieder, Marce...
SIGIR
2005
ACM
15 years 9 months ago
Question answering passage retrieval using dependency relations
State-of-the-art question answering (QA) systems employ termdensity ranking to retrieve answer passages. Such methods often retrieve incorrect passages as relationships among ques...
Hang Cui, Renxu Sun, Keya Li, Min-Yen Kan, Tat-Sen...