NLPExplorer

An Approach to Text Corpus Construction which Cuts Annotation Costs and Maintains Reusability of Annotated Data

Katrin Tomanek | Joachim Wermter | Udo Hahn |

Paper Details:

Month: June
Year: 2007
Location: Prague, Czech Republic
Venue: CoNLL | EMNLP |

Citations

URL

Stopping Criteria for Active Learning of Named Entity Recognition
Florian Laws | Hinrich Schütze |

Bringing Active Learning to Life
Ines Rehbein | Josef Ruppenhofer | Alexis Palmer |

A Comparison of Models for Cost-Sensitive Active Learning
Katrin Tomanek | Udo Hahn |

Active Learning with Amazon Mechanical Turk
Florian Laws | Christian Scheible | Hinrich Schütze |

Learning how to Active Learn: A Deep Reinforcement Learning Approach
Meng Fang | Yuan Li | Trevor Cohn |

Learning a Stopping Criterion for Active Learning for Word Sense Disambiguation and Text Classification
Jingbo Zhu | Huizhen Wang | Eduard Hovy |

Approximating Learning Curves for Active-Learning-Driven Annotation
Katrin Tomanek | Udo Hahn |

Solving the AL Chicken-and-Egg Corpus and Model Problem: Model-free Active Learning for Phenomena-driven Corpus Construction
Dain Kaplan | Neil Rubens | Simone Teufel | Takenobu Tokunaga |

Active Learning for Coreference Resolution
Florian Laws | Florian Heimerl | Hinrich Schütze |

Multi-Task Active Learning for Linguistic Annotations
Roi Reichart | Katrin Tomanek | Udo Hahn | Ari Rappoport |

Semi-Supervised Active Learning for Sequence Labeling
Katrin Tomanek | Udo Hahn |

ALTO: Active Learning with Topic Overviews for Speeding Label Induction and Document Labeling
Forough Poursabzi-Sangdeh | Jordan Boyd-Graber | Leah Findlater | Kevin Seppi |

Accelerating the Annotation of Sparse Named Entities by Dynamic Sentence Selection
Yoshimasa Tsuruoka | Jun’ichi Tsujii | Sophia Ananiadou |

Sample Selection for Statistical Parsers: Cognitively Driven Algorithms and Evaluation Measures
Roi Reichart | Ari Rappoport |

An Intrinsic Stopping Criterion for Committee-Based Active Learning
Fredrik Olsson | Katrin Tomanek |

Investigation of Unsupervised Pattern Learning Techniques for Bootstrap Construction of a Medical Treatment Lexicon
Rong Xu | Alexander A. Morgan | Amar Das | Alan Garber |

On Proper Unit Selection in Active Learning: Co-Selection Effects for Named Entity Recognition
Katrin Tomanek | Florian Laws | Udo Hahn | Hinrich Schütze |

Estimating Annotation Cost for Active Learning in a Multi-Annotator Environment
Shilpa Arora | Eric Nyberg | Carolyn P. Rosé |

A Web Survey on the Use of Active Learning to Support Annotation of Text Data
Katrin Tomanek | Fredrik Olsson |

Parallel Active Learning: Eliminating Wait Time with Minimal Staleness
Robbie Haertel | Paul Felt | Eric K. Ringger | Kevin Seppi |

A Proposal for a Configurable Silver Standard
Udo Hahn | Katrin Tomanek | Elena Beisswanger | Erik Faessler |

Analysis of Stopping Active Learning based on Stabilizing Predictions
Michael Bloodgood | John Grothendieck |

Structuring Operative Notes using Active Learning
Kirk Roberts | Sanda Harabagiu | Michael Skinner |

http://trec.nist.gov/

Field Of Study

Linguistic Trends

Syntax

Task

Corpus Annotation Tagging Chunking Named Entity Recognition Information Extraction

Language

English

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