[PDF][PDF] Unsupervised discovery of negative categories in lexicon bootstrapping
T McIntosh - Proceedings of the 2010 Conference on Empirical …, 2010 - aclanthology.org
Proceedings of the 2010 Conference on Empirical Methods in Natural …, 2010•aclanthology.org
Multi-category bootstrapping algorithms were developed to reduce semantic drift. By
extracting multiple semantic lexicons simultaneously, a category's search space may be
restricted. The best results have been achieved through reliance on manually crafted
negative categories. Unfortunately, identifying these categories is non-trivial, and their use
shifts the unsupervised bootstrapping paradigm towards a supervised framework. We
present NEG-FINDER, the first approach for discovering negative categories automatically …
extracting multiple semantic lexicons simultaneously, a category's search space may be
restricted. The best results have been achieved through reliance on manually crafted
negative categories. Unfortunately, identifying these categories is non-trivial, and their use
shifts the unsupervised bootstrapping paradigm towards a supervised framework. We
present NEG-FINDER, the first approach for discovering negative categories automatically …
Abstract
Multi-category bootstrapping algorithms were developed to reduce semantic drift. By extracting multiple semantic lexicons simultaneously, a category’s search space may be restricted. The best results have been achieved through reliance on manually crafted negative categories. Unfortunately, identifying these categories is non-trivial, and their use shifts the unsupervised bootstrapping paradigm towards a supervised framework.
We present NEG-FINDER, the first approach for discovering negative categories automatically. NEG-FINDER exploits unsupervised term clustering to generate multiple negative categories during bootstrapping. Our algorithm effectively removes the necessity of manual intervention and formulation of negative categories, with performance closely approaching that obtained using negative categories defined by a domain expert.
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