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» Statistical Relational Learning for Document Mining
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WWW
2011
ACM
14 years 4 months ago
From actors, politicians, to CEOs: domain adaptation of relational extractors using a latent relational mapping
We propose a method to adapt an existing relation extraction system to extract new relation types with minimum supervision. Our proposed method comprises two stages: learning a lo...
Danushka Bollegala, Yutaka Matsuo, Mitsuru Ishizuk...
IJCAI
2003
14 years 11 months ago
Coherent Keyphrase Extraction via Web Mining
Keyphrases are useful for a variety of purposes, including summarizing, indexing, labeling, categorizing, clustering, highlighting, browsing, and searching. The task of automatic ...
Peter D. Turney
KDD
2008
ACM
244views Data Mining» more  KDD 2008»
15 years 10 months ago
Probabilistic latent semantic visualization: topic model for visualizing documents
We propose a visualization method based on a topic model for discrete data such as documents. Unlike conventional visualization methods based on pairwise distances such as multi-d...
Tomoharu Iwata, Takeshi Yamada, Naonori Ueda
BMCBI
2011
14 years 1 months ago
BICEPP: an example-based statistical text mining method for predicting the binary characteristics of drugs
Background: The identification of drug characteristics is a clinically important task, but it requires much expert knowledge and consumes substantial resources. We have developed ...
Frank P. Y. Lin, Stephen Anthony, Thomas M. Polase...
KDD
2009
ACM
269views Data Mining» more  KDD 2009»
15 years 10 months ago
Extracting discriminative concepts for domain adaptation in text mining
One common predictive modeling challenge occurs in text mining problems is that the training data and the operational (testing) data are drawn from different underlying distributi...
Bo Chen, Wai Lam, Ivor Tsang, Tak-Lam Wong