AgriBot: Agriculture-Specific Question Answer System
AgriBot: Agriculture-Specific Question Answer System
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AgriBot：农业专用问答系统
DOI：
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
Mayank Singh
中科院分区：
文献类型：
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作者：
Naman Jain;Pranjali Jain;Pratik Kayal;Jayakrishna Sahit;Soham Pachpande;Jayesh Choudhari;Mayank Singh
印度是一个以农业为基础的经济体，关于农业做法的适当信息是实现最佳农业增长和产出的关键。为了回答农民的查询，我们基于Kisan呼叫中心的数据集构建了一个农业聊天机器人。该系统足够强大，可以回答有关天气，市场价格，植物保护和政府计划的查询。该系统24*7可用，可以通过任何电子设备访问，并且信息易于理解。该系统基于句子嵌入模型，准确率为56%。在消除同义词并结合实体提取后，准确率跃升至86%。有了这样一个系统，农民就可以更容易地了解与耕作有关的做法，从而提高农业产量。呼叫中心员工的工作将变得更容易，各种此类员工的辛勤工作可以重新定向到更好的目标。
India is an agro-based economy and proper information about agricultural practices is the key to optimal agricultural growth and output. In order to answer the queries of the farmer, we have build an agricultural chatbot based on the dataset from Kisan Call Center. This system is robust enough to answer queries related to weather, market rates, plant protection and government schemes. This system is available 24*7, can be accessed through any electronic device and the information is delivered with the ease of understanding. The system is based on a sentence embedding model which gives an accuracy of 56%. After eliminating synonyms and incorporating entity extraction, the accuracy jumps to 86%. With such a system, farmers can progress towards easier information about farming related practices and hence a better agricultural output. The job of the Call Center workforce would be made easier and the hard work of various such workers can be redirected to a better goal.