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INTELLIGENT HIV/AIDS FAQ RETRIEVAL SYSTEM USING NEURAL NETWORKS

机译:使用神经网络的智能HIV / AIDS常见问题检索系统

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In this paper, we present an HTV/AIDS FAQ retrieval using Artificial Neural Network (ANN). One of the challenges in FAQ retrieval systems is the mapping of user queries to appropriate questions in the FAQ repository so that the corresponding answer can be retrieved as an answer to the user query. To address this issue, a number of approaches have been proposed, most of which are based on traditional information retrieval techniques. In this paper we discuss our approach based on Neural Network which maps user queries to existing questions in the FAQ repository using Multi-layered Feedforward Neural Network architecture (with back-propagation training). One of the advantages of the Neural Network approach is its ability to learn based on a given training data set and then map user queries to FAQ questions based on its training. For the implementation of our neural network based FAQ Retrieval, we have experimentally determined the appropriate neural network parameters using MATLAB. To evaluate the effectiveness of the Neural Network based FAQ retrieval, we compared the performance of the system with keyword-based FAQ retrieval system. The results show a better recall and rejection of the Neural Network based approach. The experimental results demonstrate that the Neural Network approach can effectively improve the performance of the HIV/AIDS FAQ retrieval system.
机译:在本文中,我们提出了使用人工神经网络(ANN)进行HTV / AIDS常见问题的检索。 FAQ检索系统中的挑战之一是将用户查询映射到FAQ存储库中的适当问题,以便可以将相应的答案作为对用户查询的答案来检索。为了解决这个问题,已经提出了许多方法,其中大多数基于传统的信息检索技术。在本文中,我们讨论了基于神经网络的方法,该方法使用多层前馈神经网络体系结构(带有反向传播训练)将用户查询映射到FAQ库中的现有问题。神经网络方法的优点之一是能够根据给定的训练数据集进行学习,然后根据其训练将用户查询映射到FAQ问题。为了实现基于神经网络的FAQ检索,我们已经使用MATLAB通过实验确定了适当的神经网络参数。为了评估基于神经网络的FAQ检索的有效性,我们将系统的性能与基于关键字的FAQ检索系统进行了比较。结果表明,基于神经网络的方法具有更好的召回率和拒绝率。实验结果表明,神经网络方法可以有效提高HIV / AIDS FAQ检索系统的性能。

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