Case-based reasoning: business applications
Communications of the ACM
Case-based reasoning
Inside Case-Based Reasoning
Evolutionary Case Based Design
Proceedings of the First United Kingdom Workshop on Progress in Case-Based Reasoning
BLEU: a method for automatic evaluation of machine translation
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Precision and recall of machine translation
NAACL-Short '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology: companion volume of the Proceedings of HLT-NAACL 2003--short papers - Volume 2
Neural Network Language Models for Translation with Limited Data
ICTAI '08 Proceedings of the 2008 20th IEEE International Conference on Tools with Artificial Intelligence - Volume 02
Rule-based approach for handling of case markers in English to Urdu/Hindi translation
International Journal of Knowledge Engineering and Soft Data Paradigms
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In Machine Translation (MT), we reuse past translation that is encoded into a set of cases, where case is the input sentence and its corresponding translation. A case which is similar to the input sentence will be retrieved and a solution is produced by adapting its target language. The CBR approach of MT is used as a learning technique in the domain of MT of English to Sanskrit language. In our approach, syntactical feature of English language is part of the cases in the case base. The new input English sentence is matched with old cases from the stored case bases using ANN method. The retrieved case is adapted using rules. In this paper, we present the integration of CBR approach of MT with ANN and rule-based model of English to Sanskrit MT, where CBR approach of MT is used for selection of Sanskrit translation rule of input English sentence.