Enhancing Preference-Based Anaphora Resolution with Genetic Algorithms

Abstract. The paper argues that a promising way to improve the success rate of preference-based anaphora resolution algorithms is the use of machine learning. The paper outlines MARS - a program for automatic resolution of pronominal anaphors and describes an experiment which we have conducted to optimise the success rate of MARS with the help of a genetic algorithm. After the optimisation we noted an improvement up to 8% for some les. The results obtained after optimisation are discussed.

• Type: Conference
• Year: 2000
• Where: NLP
• Authors: Constantin Orasan, Richard Evans, Ruslan Mitkov
• Keywords: Anaphora Resolution Algorithms, Natural Language Processing, NLP 2000, Paper Outlines Mars, Success Rate