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基于无限城市化过程模型的城市区域功能发现与人气估计

Simultaneous Urban Region Function Discovery and Popularity Estimation Via an Infinite Urbanization Process Model
课程网址: http://videolectures.net/kdd2018_zhang_simultaneous_region/  
主讲教师: Bang Zhang
开课单位: CSIRO数学、信息学和统计学
开课时间: 2018-11-23
课程语种: 英语
中文简介:
城市化是我们在过去几十年中目睹的一种全球趋势。它给我们带来了机遇和挑战。一方面,城市系统是最复杂的社会经济系统之一,负责有效地提供满足居住、教育、娱乐、医疗等各个领域居民需求的供应,这使得城市数据分析变得困难。不同的城市区域往往呈现出不同的城市化模式,并提供不同的城市功能,例如,商业区和住宅区提供的城市功能显著不同。需要开发数据分析能力,以发现潜在的跨领域城市化模式,根据其功能相似性对城市区域进行聚类,并预测特定领域中的区域流行程度。以往在城市数据分析领域的研究往往只关注单个领域,很少考虑隐藏在不同城市区域中的跨领域城市发展模式。在本文中,我们提出了无限城市化过程(IUP)模型,用于同时发现城市区域功能和预测区域人气。IUP模型是一个生成的贝叶斯非参数过程,能够描述潜在的无限数量的城市化模式。它是在有监督的主题建模框架内开发的,并由空间区域划分空间上的一种新的分层空间距离相关贝叶斯非参数先验支持。与最先进的技术相比,在真实世界数据集上进行的实证研究显示了有希望的结果。
课程简介: Urbanization is a global trend that we have all witnessed in the past decades. It brings us both opportunities and challenges. On the one hand, urban system is one of the most sophisticated social-economic systems that is responsible for efficiently providing supplies meeting the demand of residents in various of domains, e.g., dwelling, education, entertainment, healthcare, etc. On the other hand, significant diversity and inequality exists in the development patterns of urban systems, which makes urban data analysis difficult. Different urban regions often exhibit diverse urbanization patterns and provide distinct urban functions, e.g., commercial and residential areas offer significantly different urban functions. It is desired to develop the data analytic capabilities for discovering the underlying cross-domain urbanization patterns, clustering urban regions based on their function similarity and predicting region popularity in specified domains. Previous studies in the urban data analysis area often just focus on individual domains and rarely consider cross-domain urban development patterns hidden in different urban regions. In this paper, we propose the infinite urbanization process (IUP) model for simultaneous urban region function discovery and region popularity prediction. The IUP model is a generative Bayesian nonparametric process that is capable of describing a potentially infinite number of urbanization patterns. It is developed within the supervised topic modeling framework and is supported by a novel hierarchical spatial distance dependent Bayesian nonparametric prior over the spatial region partition space. The empirical study conducted on the real-world datasets shows promising outcome compared with the state-of-the-art techniques.
关 键 词: 无限城市化过程模型; 城市区域功能发现; 人气估计
课程来源: 视频讲座网
数据采集: 2023-03-09:cyh
最后编审: 2023-05-15:cyh
阅读次数: 20