Authors: Džunić, Zoran
Momčilović, Svetislav
Todorović, Branimir
Stanković, Miomir 
Title: Conference resolution using decision trees
Journal: 8th Seminar on Neural Network Applications in Electrical Engineering, Neurel-2006 Proceedings
First page: 109
Last page: 114
Issue Date: 1-Dec-2006
ISBN: 1-4244-0433-9
DOI: 10.1109/NEUREL.2006.341188
Abstract: 
Corefence resolution is the process of determining whether two expressions in natural language refer to the same entity in the world. We adopt machine learning approach using decision tree to a coreference resolution of general noun phrases in unrestricted text based on well defined features. We also use approximate matching algorithms for a string match feature and databases of American last names and male and female first names for gender agreement and alias feature. For the evaluation we use MUC-6 coreference corpora. We show that pessimisitc error pruning method gives better generalization in a coreference resolution task than that reported in Soon et al. [20], when weights of positive and negative examples are properly chosen.
Keywords: Approximate string matching | Coreference resolution | Decision tree | Machine learning | Pessimistic error pruning
Publisher: IEEE

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