基于知识图谱的包装领域智能问答系统的设计

目的 针对目前包装产业存在的产业链长、数据大而散、包装领域知识信息检索不精准等问题,设计一个基于知识图谱的包装领域智能问答系统.方法 采用知识图谱、智能问答、自然语言处理、深度学习和个性化推荐等技术,对互联网上各类包装领域数据进行采集汇聚、抽取知识、融合计算,最终形成一个包装领域混合型智能问答系统.结果 系统主要功能包括知识图谱、文本相似匹配、图像识别和自动问答,实现了包装领域大数据的知识卡片、语义搜索和沉浸问答.结论 该系统使用方便,通过问答方式,一站式快速按需获取多视图、多维度包装领域数据,提升了行业的数字化、信息化和智能化水平.

Design of Intelligent Question-Answering System for Packaging Field Based on Knowledge Graph

The project aims to design an intelligent question-answering system for packaging field based on knowledge graph to solve the problems existing in the packaging industry, such as the long industrial chain, large and scattered data, and inaccurate knowledge information retrieval. Techniques such as knowledge graph, intelligent question-answering, natural language processing, deep learning, and personalized recommendation have been adopted for the collection and aggregation, knowledge extraction, and fusion computing on various packaging data on the Internet. A hybrid intelligent question-answering system for packaging field is finally formed. The main functions of the system include knowledge graph, text similarity matching, image recognition and automatic question-answering, which realizes the knowledge card, semantic search and immersive question-answering of big data in the packaging field. With the system, it is handy to obtain the packaging-relevant data on-demand from multi-view and multi-dimension at one-stop in no time through the question-answering mode, thus, enabling the industry to be digitized, information-based, and intelligent.