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material ID: featurespace

Related Papers

A Systematic Exploration of the Feature Space for Relation Extraction

Authors: nan

Publication: TIPSTER (2007)

DOI: nan

Relation extraction is the task of find- ing semantic relations between entities from text. The state-of-the-art methods for relation extraction are mostly based on statistical learning, and thus all have …...

24169

Interactive Feature Space Construction using Semantic Information

Authors: nan

Publication: TIPSTER (2009)

DOI: nan

Specifying an appropriate feature space is an important aspect of achieving good perfor- mance when designing systems based upon learned classifiers. Effectively incorporat- ing information regarding semantically related words into …...

42344

Assessing Benefit from Feature Feedback in Active Learning for Text Classification

Authors: nan

Publication: TIPSTER (2011)

DOI: nan

Feature feedback is an alternative to instance labeling when seeking supervision from hu- man experts. Combination of instance and feature feedback has been shown to reduce the total annotation cost …...

42283

Learning a hierarchy of specialized pairwise models for coreference resolution (Apprentissage d’une hiérarchie de modèles à paires spécialisés pour la résolution de la coréférence) [in French]

Authors: nan

Publication: TIPSTER (2013)

DOI: nan

Learning a hierarchy of specialized pairwise models for coreference resolution This paper proposes a new method for significantly improving the performance of pairwise coreference models. Given a set of indicators, …...

1939

An Off-the-shelf Approach to Authorship Attribution

Authors: nan

Publication: TIPSTER (2014)

DOI: nan

Authorship detection is a challenging task due to many design choices the user has to decide on. The performance highly depends on the right set of features, the amount of …...

5844

Less Is Better: Recovering Intended-Feature Subspace to Robustify NLU Models

Authors: nan

Publication: TIPSTER (2022)

DOI: nan

AbstractDatasets with significant proportions of bias present threats for training a trustworthy model on NLU tasks. Despite yielding great progress, current debiasing methods impose excessive reliance on the knowledge of …...

5074