AUTO TRANSFORMATION OF NETWORK DATA MODELS USING NEURAL MACHINE TRANSLATION

Described herein are systems and methods for neural machine translation (NMT) of languages between network operation systems. The languages may be a query language, such as a XML path, to navigate through elements and attributes in an XML document. An NMT model comprises an encoder and a decoder to implement the machine translation. The encoder encodes a source sentence as a sequence of encoder hidden states. The decoder may incorporate attention mechanism to generate a target sentence, conditioned on the encoder hidden states. The NMT model may also use a modified beam search with variable beam width and search scope for each search step to speed up search process with a balance of accuracy and processing cost. Evaluation results demonstrate that embodiments of the present disclosure may be used in a recommender system for XPath auto-generation between different network operation systems.