We consider in this paper deploying external knowledge transfer inside a simple double agent Viterbi algorithm which is an algorithm firstly introduced by the author in his preprint "Hidden Markov Based Mathematical Model dedicated to Extract Ingredients from Recipe Text". The key challenge of this work lies in discovering the reason why our old model does have bad performances when it is confronted with estimating ingredient state for unknown words and see if deploying external knowledge transfer directly on calculating state matrix could be the solution instead of deploying it only on back propagating step.
翻译:在本文中,我们认为,将外部知识转让放在一个简单的双重代理人Viterbi算法中,这是作者在“Hidden Markov 基础数学模型”的预印本中首先采用的算法,该模型专门用来从食谱文本中提取成份。 这项工作的主要挑战在于发现为什么我们的旧模型在用未知的单词估算成份状态时确实表现不佳,并且看看直接在计算状态矩阵上部署外部知识转让是否是一种解决办法,而不是仅仅在背面传播步骤上部署。