Hybrid learning of Syntactic and Semantic Dependencies
Abstract
This paper presents our solution for jointly parsing of syntactic and semantic dependencies. The Maximum Entropy (ME) classifier is selected in this system. Also the Mutual Information (MI) model was utilized into feature selection of dependency labeling. Results show that the MI model allows the system to get better performance and reduce training hours.
This work is licensed under a Creative Commons Attribution 3.0 License.
Computer and Information Science ISSN 1913-8989 (Print) ISSN 1913-8997 (Online)
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Computer and Information Science


