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» Semi-supervised Learning from General Unlabeled Data
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CIKM
2009
Springer
14 years 2 months ago
Learning to rank from Bayesian decision inference
Ranking is a key problem in many information retrieval (IR) applications, such as document retrieval and collaborative filtering. In this paper, we address the issue of learning ...
Jen-Wei Kuo, Pu-Jen Cheng, Hsin-Min Wang
AAAI
1998
13 years 9 months ago
Learning to Extract Symbolic Knowledge from the World Wide Web
The World Wide Web is a vast source of information accessible to computers, but understandable only to humans. The goal of the research described here is to automatically create a...
Mark Craven, Dan DiPasquo, Dayne Freitag, Andrew M...
PAMI
2010
122views more  PAMI 2010»
13 years 6 months ago
Domain Adaptation Problems: A DASVM Classification Technique and a Circular Validation Strategy
—This paper addresses pattern classification in the framework of domain adaptation by considering methods that solve problems in which training data are assumed to be available o...
Lorenzo Bruzzone, Mattia Marconcini
EMNLP
2011
12 years 7 months ago
Learning Sentential Paraphrases from Bilingual Parallel Corpora for Text-to-Text Generation
Previous work has shown that high quality phrasal paraphrases can be extracted from bilingual parallel corpora. However, it is not clear whether bitexts are an appropriate resourc...
Juri Ganitkevitch, Chris Callison-Burch, Courtney ...
ICML
2006
IEEE
14 years 8 months ago
Ranking on graph data
In ranking, one is given examples of order relationships among objects, and the goal is to learn from these examples a real-valued ranking function that induces a ranking or order...
Shivani Agarwal