Text-Based Intent Analysis using Deep Learning

Vraj Desai, Sidarth Wadhwa, A. Anurag, Bhisham Bajaj
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引用次数: 1

Abstract

Intent classification focuses on analyzing input to gauge the users’ needs and opinions. With this proposed system, we utilise a neural network classifier that analyzes text strings that are fed to it as input. Based on the analyzed intent, the system responds to the user by acting upon the commands issued to it. The areas covered by the system include weather, ratings, and booking restaurants. Firstly the intent of the text will be analysed and then it will be classified based on the topic it belongs to. Due to expressiveness of intent by users intent , for instance ”need a rental space”, ”places to visit in chennai” intent analysis plays a major role in ecommerce, real estate and online marketing industry. We aim to maximize the accuracy and minimize the errors and the time complextity of the proposed system
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基于文本的深度学习意图分析
意图分类侧重于分析输入,以衡量用户的需求和意见。在这个系统中,我们使用一个神经网络分类器来分析作为输入的文本字符串。基于分析的意图,系统通过执行用户发出的命令来响应用户。该系统覆盖的领域包括天气、评级和预订餐厅。首先分析文本的意图,然后根据其所属的主题对其进行分类。由于用户意图的表达性,例如“需要租用空间”,“在金奈参观的地方”,意图分析在电子商务,房地产和在线营销行业中发挥着重要作用。我们的目标是最大限度地提高准确度,最小化误差和时间复杂度
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