基于python的开放领域事件抽取系统设计与实现

摘 要

Python技术的发展让更多科学、信息化的事件成为了可能，各种信息技术的发展也赢得了一次更高的推送，各种行为、动作、场景的分析抽取，也让我们的生活得到了更加便利的操作，每一次信息技术的改变都在影响着社会、生活、时代的变化。电子商务出现了，淘宝、天猫、物流行业的兴起，让我们可以买到各个地方的东西；信息技术发展WEB信息化的到来让人们的生活感受到了科技带来的便利，不认识的地方导航就可以找到，没去过的旅游景点线上就可以看到等等；数字化技术的发展给各种各样的企业带来了福音，智能制造、数字化转型给企业的发展提供技术型的力量。这些仅仅是平常接触到的场景，更有些更深入的算法场景更是改变人们的生活，就拿出行最多使用到的导航算法而言，不同时刻所需要的时间及路况也是大不相同的，没有强大的算法功能支持这些都是很难做到的。这次我们的设计所做的应用也是根据现实生活当中的需求来进行针对性的功能解决的，所有的业务也好，功能啥的都是根据实际的需求设计而来。为了满足客户个性化需求,增加客户粘性,实现产品的快速更新迭代,需要收集分析客户反馈信息,面临着快速处理客户反馈的挑战。然而人工分析处理文本效率较低,这就迫切需要自动地从非结构化的客户反馈数据中提取出关键信息。如何利用人工智能技术自动地从非结构化的文本数据中提取出结构化的信息,发掘出对于用户具有潜在价值的数据,成为自然语言处理的一项重要且复杂的任务。信息抽取的提出就是为了完成此类任务。事件抽取是信息抽取的一个重要研究方向，从文档中抽取出事件信息，包括人物、时间、地点的结构化信息，最终存储到数据库形成知识库,共信息检索、问答等上层应用。
这次的事件抽取信息管理系统的实现呢是依靠JS语言来进行实现的，那么这次的后台设计主要还是以python语言为主体系，这样一来日后的升级或者需要问题时可以通过多种多样的途径来进行解决，毕竟还是开源的体系。其次，后台管理实现呢还是采用B/S的设计模式，这样的设计模式可以通过浏览器访问，不用安装任何东西。当然数据的保存等方面也是采用MYSQL来进行的。
关键字：事件抽取 MYSQL python语言，

Design and implementation of python Open Domain Event Extraction system
Abstract
The development of Python technology makes more scientific and information events possible, and the development of various information technologies also wins a higher push. The analysis and extraction of various behaviors, actions and scenes also make our life more convenient to operate. Every change of information technology is affecting the change of society, life and times. The emergence of e-commerce, Taobao, Tmall, the rise of the logistics industry, so that we can buy things from various places; The advent of WEB information technology makes people feel the convenience brought by science and technology in their lives. They can find the places they do not know by navigation, and see the tourist attractions they have not been to online. The development of digital technology has brought good news to all kinds of enterprises. Intelligent manufacturing and digital transformation provide technological strength to the development of enterprises. These are just ordinary scenes, and some more in-depth algorithm scenes are changing people’s lives. As for the navigation algorithm used most in travel, the time and road conditions required at different moments are also very different, and it is difficult to do without powerful algorithm functions to support these. This time, the application of our design is also based on the needs of real life to carry out targeted functional solutions, all the business is good, what function is designed according to the actual needs. In order to meet the personalized needs of customers, increase customer stickiness, and realize the rapid update and iteration of products, it is necessary to collect and analyze customer feedback information, which is faced with the challenge of quickly processing customer feedback. However, manual analysis of text is inefficient, which makes it imperative to automatically extract key information from unstructured customer feedback data. How to use artificial intelligence technology to automatically extract structured information from unstructured text data and discover data with potential value for users has become an important and complex task in natural language processing. Information extraction is proposed to accomplish this kind of task. Event extraction is an important research direction of information extraction, extracting event information from documents, including structured information about people, time and place, and finally storing it in a database to form a knowledge base for upper-level applications such as information retrieval and question and answer.
The implementation of the college student employment information management system is to rely on JS language to achieve, so the background design is mainly based on the python language system, so that the future upgrade or need problems can be solved through a variety of ways, after all, or open source system. Secondly, the background management implementation is still using the B/S design pattern, such a design pattern can be accessed through the browser, without installing anything. Of course, data preservation and other aspects are also used to carry out MYSQL.

Key words: Employment of college students MYSQL python language

目 录
Design and implementation of python Open Domain Event Extraction system 1
Abstract 1
目 录 3
1 绪 论 4
1.1 课题研究背景及意义 4
1.2 选题研究的内容以及主要目标 4
1.2.1研究目标 4
1.2.2研究思路 1
1.2.3研究方法 1
1.2.4研究现状 2
1.3论文目录结构 2
2 相关工具及技术说明 3
2.1 B/S访问结构 3
2.2 Django框架简介 3
2.3 MySQL数据库 3
2.4 Python语言介绍 4
3 需求分析 4
3.1非功能性需求分析 4
3.3系统功能需求 4
4 可行性分析 5
4.1 可行性分析 5
4.1.1　时间可行性 5
4.2.2 经济可行性 5
4.1.3 操作可行性 1
4.1.4 法律可行性 1
4 数据库设计 1
4.1 E-R图 1
4.2设计原则 1
4.3 数据库设计 1
5 系统功能实现 1
5.1 系统实现 1
5.1.1 登录页面 1
5.1.2 后台管理页面 2
5.1.3 后台首页 1
5.1.4 用户管理 1
致　　谢 0
参考文献 1