为印度农民打造24小时农业问答机器人，精准解答农事问题。
Agribot: agriculture-specific question answer system
- 基于句子嵌入模型，结合实体识别与同义词消减提升准确率。
- 准确率从56%提升至86%，覆盖天气、行情、植保和政策等场景。
- 适合农村地区农民及农业服务人员使用，降低信息获取门槛。
印度是农业经济主导的国家，掌握正确的农业实践信息对实现农业高效增长至关重要。为帮助农民解答各类疑问，我们基于克里桑呼叫中心的数据集构建了一个农业聊天机器人系统。该系统可全天候运行，通过任意电子设备访问，信息呈现通俗易懂。系统采用句子嵌入模型，初始准确率为56%；经去除同义词并引入实体提取后，准确率提升至86%。系统支持回答天气、市场行情、植物保护及政府补贴政策等多类问题，有助于农民更便捷地获取农事信息，从而提高农业生产效率。同时，也能减轻呼叫中心工作人员负担，使其工作重心转向更高价值任务。
原文摘要 · Abstract (English)
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.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。