基于特征选择与关联规则挖掘分析无家可归者需求
Analysing the Needs of Homeless People Using Feature Selection and Mining Association Rules
AI总结：
本文提出SINTECH项目，通过移动应用收集无家可归者数据，并利用特征选择与关联规则挖掘等人工智能技术识别关键特征和关联规则，以支持非政府组织更高效地帮助无家可归者。
摘要：
无家可归是一个在欧洲具有重大影响的社会与健康问题。许多非政府组织通过收集并分析有关无家可归者的大量信息来帮助他们。然而，这些任务并不总是容易执行，并且会妨碍组织的其他职责。SINTECH项目正是为解决这一问题而设立，提出了两种不同的工具：一个用于快速便捷地收集数据的移动应用程序；以及一个基于人工智能的软件，用于从收集到的数据中获取有价值的信息。前者已分发给一些西班牙组织，这些组织正在使用它对无家可归者进行调查。第二个工具实现了不同的特征选择方法和关联规则挖掘方法。这些人工智能技术使我们能够从先前收集的无家可归者数据中识别出最相关的特征以及一些有趣的关联规则。
英文摘要：
Homelessness is a social and health problem with great repercussions in Europe. Many non-governmental organisations help homeless people by collecting and analysing large amounts of information about them. However, these tasks are not always easy to perform, and hinder other of the organisations duties. The SINTECH project was created to tackle this issue proposing two different tools: a mobile application to quickly and easily collect data; and a software based on artificial intelligence which obtains interesting information from the collected data. The first one has been distributed to some Spanish organisations which are using it to conduct surveys of homeless people. The second tool implements different feature selection and association rules mining methods. These artificial intelligence techniques have allowed us to identify the most relevant features and some interesting association rules from previously collected homeless data.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
