2007 PredictingStructuredData

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Subject Headings: Structured Data Prediction


Cited By

~54 http://scholar.google.com/scholar?cites=5990074176453302677


Book overview

  • Machine learning develops intelligent computer systems that are able to generalize from previously seen examples. A new domain of machine learning, in which the prediction must satisfy the additional constraints found in structured data, poses one of machine learning’s greatest challenges: learning functional dependencies between arbitrary input and output domains. This volume presents and analyzes the state of the art in machine learning algorithms and theory in this novel field. The contributors discuss applications as diverse as machine translation, document markup, computational biology, and information extraction, among others, providing a timely overview of an exciting field.



 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
2007 PredictingStructuredDataGökhan H. Bakir
Thomas Hofmann
Bernhard Schölkopf
Predicting Structured DataMIT Presshttp://books.google.com/books?id=b1EFKUoFF8IC2007