Proceedings of the 3rd ACM SIGSPATIAL Workshop on Smart Cities and Urban Analytics最新文献_第2页

Predictive Analytics Using Text Classification for Restaurant Inspections 使用文本分类进行餐馆检查的预测分析

Proceedings of the 3rd ACM SIGSPATIAL Workshop on Smart Cities and Urban Analytics Pub Date : 2017-11-07 DOI: 10.1145/3152178.3152192

Zhu Wang, B. Balasubramani, I. Cruz

引用次数: 7

Using Yelp to Find Romance in the City: A Case of Restaurants in Four Cities 使用Yelp在城市中寻找浪漫:以四个城市的餐馆为例

Proceedings of the 3rd ACM SIGSPATIAL Workshop on Smart Cities and Urban Analytics Pub Date : 2017-11-07 DOI: 10.1145/3152178.3152181

S. Rahimi, Clio Andris, Xi Liu

{"title":"Using Yelp to Find Romance in the City: A Case of Restaurants in Four Cities","authors":"S. Rahimi, Clio Andris, Xi Liu","doi":"10.1145/3152178.3152181","DOIUrl":"https://doi.org/10.1145/3152178.3152181","url":null,"abstract":"Romantic relationships are an understudied aspect of cities and the built environment. Yet, restaurants continue to attract couples and augment the landscape with visible signs of affection at a table for two---or more. User-generated content (UGC) of restaurant reviews from online review site Yelp (http://yelp.com) provide text on romantic keywords such as \"date\", \"love\", \"boyfriend\", \"wife\", \"anniversary\", \"family\" by geolocated restaurants. We use these to distinguish restaurants and discover features of restaurants associated with various romantic keywords. These features include restaurant ratings and location, as well as comments about the ambiance, food, service, etc. Using data from the Yelp Dataset Challenge in U.S. cities Charlotte, NC, Las Vegas, NM, Phoenix, AZ, and Pittsburgh, PA, we employ different data mining and correlation tools as well as GIS modeling to learn more about what types of romantic relationships use which parts of the city, and how their choices of restaurants differ by relationship stage. We find that families prefer restaurants that are outside of the central business district (CBD), have good service and high-rated food, while couples---married or dating---prefer hot spots with great ambiance for nightlife. We also find that inexpensive food is not associated with romantic dates, and the quality of service also plays a secondary role to a \"classy\" and \"cozy\" atmosphere.","PeriodicalId":378940,"journal":{"name":"Proceedings of the 3rd ACM SIGSPATIAL Workshop on Smart Cities and Urban Analytics","volume":"118 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125549628","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

The Relationship between Timing of Development and Bus Rapid Transit 发展时机与快速公交的关系

Proceedings of the 3rd ACM SIGSPATIAL Workshop on Smart Cities and Urban Analytics Pub Date : 2017-11-07 DOI: 10.1145/3152178.3152194

Klara Bergman, J. Franklin, T. Gadda, N. P. Kozievitch

{"title":"The Relationship between Timing of Development and Bus Rapid Transit","authors":"Klara Bergman, J. Franklin, T. Gadda, N. P. Kozievitch","doi":"10.1145/3152178.3152194","DOIUrl":"https://doi.org/10.1145/3152178.3152194","url":null,"abstract":"The city of Curitiba in southern Brazil is considered to be the cradle of the Bus Rapid Transit (BRT) system. Curitiba has a population of around 1.9 million people and has a higher development index than Brazil in general. A master plan approved in the middle of the 1960's has guided the development of the city in a Transit Oriented Development (TOD) direction by zoning for high development densities close to the five BRT trunk lines in so-called structural development in Curitiba. The objective was to examine if the BRT system could have been a motivator for property development, and if so, to what extend. This paper presents a perspective to examine property development: Timing of Development, as the relationship between the number of years after construction of BRT lines buildings were constructed, and the distances of these buildings from the BRT lines. Results from the entire BRT system showed that a greater \"time lag\" of property development following BRT development also meant that the property in question was located further away from a BRT line, suggesting that areas close to the BRT were popular.","PeriodicalId":378940,"journal":{"name":"Proceedings of the 3rd ACM SIGSPATIAL Workshop on Smart Cities and Urban Analytics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129228116","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Rapid development of semantic 3D city models for urban energy analysis based on free and open data sources and software 基于自由开放数据源和软件的城市能源分析语义三维城市模型的快速发展

Proceedings of the 3rd ACM SIGSPATIAL Workshop on Smart Cities and Urban Analytics Pub Date : 2017-11-07 DOI: 10.1145/3152178.3152193

Jochen Wendel, A. Simons, A. Nichersu, Syed Monjur Murshed

{"title":"Rapid development of semantic 3D city models for urban energy analysis based on free and open data sources and software","authors":"Jochen Wendel, A. Simons, A. Nichersu, Syed Monjur Murshed","doi":"10.1145/3152178.3152193","DOIUrl":"https://doi.org/10.1145/3152178.3152193","url":null,"abstract":"Geospatial data, specifically semantic 3D building data, plays a crucial role in urban energy analysis as spatial calculations using 3D geometries usually form the basis for energy simulation and modelling needed for numerous smart cities applications. Additional information describing the building stock, such as building materials and energetic properties but also data not directly linked to urban morphology such as weather data, environmental data, vegetation or socio-demographic data sets are required for these applications. A major drawback in the widespread applicability of urban energy analysis is the lack of available data sets as well as the costly and lengthy labor-intensive process of generation of those data sets (e.g. 3D city models or LIDAR data). While recent years have seen an opening up of urban data sets through free and open data portals, web services, and APIs that are used for urban energy analysis, data standardization and varying data quality still raises big challenges. This research explores different methodologies for the generation and usage of semantic 3D city models based on free and open data sources and software. In this paper, we describe four different methodologies for the generation of semantic 3D city models from available open data (geospatial data portals, LIDAR data, Open Street Map data, and remote sensing) and the tools required to achieve the task. To evaluate the suitability of these open-data sets for smart cities applications, multiple energy models, such as an energy performance model and a vertical solar radiation tool, previously developed in EIFER, have been applied to evaluate the applicability of these generated city models.","PeriodicalId":378940,"journal":{"name":"Proceedings of the 3rd ACM SIGSPATIAL Workshop on Smart Cities and Urban Analytics","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131047750","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 11

Towards a hybrid framework for the visualization and analysis of 3D spatial data 一个用于三维空间数据可视化和分析的混合框架

Proceedings of the 3rd ACM SIGSPATIAL Workshop on Smart Cities and Urban Analytics Pub Date : 2017-11-07 DOI: 10.1145/3152178.3152183

A. Graciano, Antonio J. Rueda Ruiz, L. Ortega, F. Feito-Higueruela

{"title":"Towards a hybrid framework for the visualization and analysis of 3D spatial data","authors":"A. Graciano, Antonio J. Rueda Ruiz, L. Ortega, F. Feito-Higueruela","doi":"10.1145/3152178.3152183","DOIUrl":"https://doi.org/10.1145/3152178.3152183","url":null,"abstract":"Several geospatial problems like urban subsurface analysis involve data from multiple domains and nature. For instance, an urban infrastructure analysis must take into account not only the urban elements but their geological environment. This requires the definition of hybrid schemes and algorithms that keep the dimensionality and domain of the data, while allowing the joint management of both representations in a combined way. In addition, a proper 3D visualization method that shows those heterogeneous data together can be very useful for geoscientific and GIS professionals. In this paper, we present the foundations of a real-time 3D visualization framework capable of rendering field and vector data, as well as a set of operations that can solve many problems for engaging data from different domains. We propose the use of the Stack-Based Representation of Terrains for field data which provides a whole 3D representation of volumetric terrains while allowing an efficient memory usage. The resulting hybrid framework can help geoscientists and engineers to analyze 3D complex geospatial data and make decisions at a glance.","PeriodicalId":378940,"journal":{"name":"Proceedings of the 3rd ACM SIGSPATIAL Workshop on Smart Cities and Urban Analytics","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129533956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Real-Time Bayesian Micro-Analysis for Metro Traffic Prediction 地铁交通预测的实时贝叶斯微分析

Proceedings of the 3rd ACM SIGSPATIAL Workshop on Smart Cities and Urban Analytics Pub Date : 2017-11-07 DOI: 10.1145/3152178.3152190

Eric Lin, Jinhyung D. Park, Andreas Züfle

{"title":"Real-Time Bayesian Micro-Analysis for Metro Traffic Prediction","authors":"Eric Lin, Jinhyung D. Park, Andreas Züfle","doi":"10.1145/3152178.3152190","DOIUrl":"https://doi.org/10.1145/3152178.3152190","url":null,"abstract":"Metro transport plays a large role in major cities around the world as an easily accessible and convenient means of transit. We propose a novel approach to forecast the metro network flow of passengers, which is exceptionally useful for city planning. For instance, accurate estimations of passenger outflow provide valuable insight in deciding where and when to add new trains and stations. We present a micro-prediction approach to predict individual passenger's destination station and arrival time. As a global apriori model we empirically learn a probability distribution of origin-destination (OD) station-pairs using analysis on historical data and estimate travel times between stations. Then, we condition the OD probability distribution by the current travel time of an individual passenger using Bayesian learning. For each station, the summation of the probability distribution of each passenger in the network produces the expected outflow. Our experimental evaluation shows that our model outperforms baseline approaches, thus showing that our model can be successfully implemented for a wide array of passenger traffic flow data for smart city planning.","PeriodicalId":378940,"journal":{"name":"Proceedings of the 3rd ACM SIGSPATIAL Workshop on Smart Cities and Urban Analytics","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125365653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Proceedings of the 3rd ACM SIGSPATIAL Workshop on Smart Cities and Urban Analytics 第三届ACM sigspace智慧城市与城市分析研讨会论文集

Proceedings of the 3rd ACM SIGSPATIAL Workshop on Smart Cities and Urban Analytics Pub Date : 2016-10-31 DOI: 10.1145/3152178

H. Vo

引用次数: 1