Proceedings of the 28th International Conference on Advances in Geographic Information Systems最新文献_第7页

Efficient Downscaling of Satellite Oceanographic Data With Convolutional Neural Networks 基于卷积神经网络的卫星海洋数据降尺度研究

Proceedings of the 28th International Conference on Advances in Geographic Information Systems Pub Date : 2020-11-03 DOI: 10.1145/3397536.3429335

N. Saxena

引用次数: 1

Optimizing Continuous kNN Queries over Large-Scale Spatial-Textual Data Streams 优化大规模空间文本数据流上的连续kNN查询

Proceedings of the 28th International Conference on Advances in Geographic Information Systems Pub Date : 2020-11-03 DOI: 10.1145/3397536.3422225

Rong Yang, Baoning Niu

{"title":"Optimizing Continuous kNN Queries over Large-Scale Spatial-Textual Data Streams","authors":"Rong Yang, Baoning Niu","doi":"10.1145/3397536.3422225","DOIUrl":"https://doi.org/10.1145/3397536.3422225","url":null,"abstract":"The continuous k-Nearest Neighbor queries over spatial-textual data streams (abbr. CkQST) retrieve and continuously monitor at most k nearest neighbor (abbr. kNN) objects to the user-specified location containing all the user-specified keywords, which is the core operation of numerous location-based publish/subscribe systems. Such a system is usually subscribed with a massive number of CkQST and evaluated simultaneously whenever new objects are incoming and old objects are expiring. The approach to evaluating CkQST is to construct a spatial-textual hybrid index for subscribed queries and matching the incoming objects utilizing the filtering capabilities of the index. For CkQST, the minimal spatial search range covering kNN objects changes frequently with the arrival and expiration of qualified objects, and the cost of updating the index is prohibitively high. To efficiently evaluate CkQST, we extend Quad-tree with an inverted index, and exploit it with three techniques, i.e. a memory-based cost model, a block-based ordered inverted index and an adaptive insertion strategy. The experiments on comprehensive datasets demonstrate the effectiveness and efficiency of our proposed techniques.","PeriodicalId":233918,"journal":{"name":"Proceedings of the 28th International Conference on Advances in Geographic Information Systems","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131602185","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

POI Atmosphere Categorization Using Web Search Session Behavior 使用Web搜索会话行为的POI气氛分类

Proceedings of the 28th International Conference on Advances in Geographic Information Systems Pub Date : 2020-11-03 DOI: 10.1145/3397536.3422196

K. Tsubouchi, Hayato Kobayashi, Toru Shimizu

{"title":"POI Atmosphere Categorization Using Web Search Session Behavior","authors":"K. Tsubouchi, Hayato Kobayashi, Toru Shimizu","doi":"10.1145/3397536.3422196","DOIUrl":"https://doi.org/10.1145/3397536.3422196","url":null,"abstract":"Point Of Interest (POI) categorization is to group POIs into several categories and make them easy-to-use in geospatial applications. Previous studies mainly used geospatial features, such as check-in sequences and satellite images, to group POIs into pre-defined rough categories. However, each POI has its own \"atmosphere\" beyond its geospatial features, which represents what kinds of people tend to visit it and how they spend their time there. This subtle atmosphere is important for users to decide whether to visit the POI, so considering it may be critical when providing commercial services, such as a property search service. In this paper, we propose a new POI categorization method that can capture the POI atmosphere by using user behavior on a web search engine. Our key observation is that the next queries of a search query about a POI tend to contain the user's purpose for visiting it. We harness this observation to train a neural encoder that maps POIs to continuous vectors (called embeddings) via next-query prediction with a deep structured semantic model (DSSM). Experimental results indicate that our method performs well for POI atmosphere categorization of parks as a case study. We believe that our method complements the existing POI categorization methods.","PeriodicalId":233918,"journal":{"name":"Proceedings of the 28th International Conference on Advances in Geographic Information Systems","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114612934","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: 1

A Geospatial Analytics Approach to Delineate Trade Areas for Quick Service Restaurants (QSR) in Singapore 地理空间分析方法在新加坡划定快餐店(QSR)贸易区域

Proceedings of the 28th International Conference on Advances in Geographic Information Systems Pub Date : 2020-11-03 DOI: 10.1145/3397536.3428352

L. Ting

引用次数: 0

Node-attributed Spatial Graph Partitioning 节点属性空间图分区

Proceedings of the 28th International Conference on Advances in Geographic Information Systems Pub Date : 2020-11-03 DOI: 10.1145/3397536.3422198

Daniel Bereznyi, Ahmad Qutbuddin, Y. Her, Kwangsoo Yang

{"title":"Node-attributed Spatial Graph Partitioning","authors":"Daniel Bereznyi, Ahmad Qutbuddin, Y. Her, Kwangsoo Yang","doi":"10.1145/3397536.3422198","DOIUrl":"https://doi.org/10.1145/3397536.3422198","url":null,"abstract":"Given a spatial graph and a set of node attributes, the Node-attributed Spatial Graph Partitioning (NSGP) problem partitions a node-attributed spatial graph into k homogeneous sub-graphs that minimize both the total RMSErank1 and edge-cuts while meeting a size constraint on the sub-graphs. RMSErank1 is the Root Mean Square Error between a matrix and its rank-one decomposition. The NSGP problem is important for many societal applications such as identifying homogeneous communities in a spatial graph and detecting interrelated patterns in traffic accidents. This problem is NP-hard; it is computationally challenging because of the large size of spatial graphs and the constraint that the sub-graphs must be homogeneous, i.e. similar in terms of node attributes. This paper proposes a novel approach for finding a set of homogeneous sub-graphs that can minimize both the total RMSErank1 and edge-cuts while meeting the size constraint. Experiments and a case study using U.S. Census datasets and HP#6 watershed network datasets demonstrate that the proposed approach partitions a spatial graph into a set of homogeneous sub-graphs and reduces the computational cost.","PeriodicalId":233918,"journal":{"name":"Proceedings of the 28th International Conference on Advances in Geographic Information Systems","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120963360","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

Smartmedia

Proceedings of the 28th International Conference on Advances in Geographic Information Systems Pub Date : 2020-11-03 DOI: 10.1145/3397536.3422338

Y. Kanza, D. Gibbon, D. Srivastava, Valerie Yip, E. Zavesky

{"title":"Smartmedia","authors":"Y. Kanza, D. Gibbon, D. Srivastava, Valerie Yip, E. Zavesky","doi":"10.1145/3397536.3422338","DOIUrl":"https://doi.org/10.1145/3397536.3422338","url":null,"abstract":"Streaming media is gaining popularity, with numerous new services for video on demand and live broadcast. These services stream requested media content to user devices like smart TVs, personal computers and smartphones. Many of these devices are mobile devices, yet streaming media services do not adapt the delivered content to the context of the request, e.g., the location of the user, the time of the request or who are the people near the viewer. In this paper we illustrate how geofencing and geoblocking can be combined with adaptive streaming media to create a new technology of contextually-adapted streaming media. The new technology has the potential to create a new type of experience for streaming media by applying real-time modification of streamed content according to the viewer and the context, e.g., modify inappropriate content when the media is played in public places, change the length of a video played by a train passenger according to a train schedule, etc. The suggested technology can also be used for preventing password sharing in a non-intrusive way and for hyperlocal geoblocking, to facilitate copyright protection. We discuss the vision of modifying streaming media in real time based on the context, elaborate on some of the challenges in implementing this vision, and present novel applications of this new technology.","PeriodicalId":233918,"journal":{"name":"Proceedings of the 28th International Conference on Advances in Geographic Information Systems","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115057930","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

Semantically Augmented Range Queries over Heterogeneous Geospatial Data 异构地理空间数据的语义扩展范围查询

Proceedings of the 28th International Conference on Advances in Geographic Information Systems Pub Date : 2020-11-03 DOI: 10.1145/3397536.3422271

Goce Trajcevski, B. Balasubramani, I. Cruz, R. Tamassia, Xu Teng

引用次数: 0

Route Reconstruction Using Low-Quality Bluetooth Readings 使用低质量蓝牙读数进行路由重建

Proceedings of the 28th International Conference on Advances in Geographic Information Systems Pub Date : 2020-11-03 DOI: 10.1145/3397536.3422224

Yehong Xu, Dan He, P. Chao, Jiwon Kim, Wen Hua, Xiaofang Zhou

{"title":"Route Reconstruction Using Low-Quality Bluetooth Readings","authors":"Yehong Xu, Dan He, P. Chao, Jiwon Kim, Wen Hua, Xiaofang Zhou","doi":"10.1145/3397536.3422224","DOIUrl":"https://doi.org/10.1145/3397536.3422224","url":null,"abstract":"Route reconstruction targets at recovering the actual routes of objects moving on an underlying road network from their times-tamped position measurements. This fundamental pre-processing step to many location-based applications has been extensively studied for GPS data, which are object-centric and relatively densely sampled data. In this paper, we investigate the problem of route reconstruction using data collected from road-side Bluetooth scanners. In many cities, Bluetooth scanners are installed in road networks for monitoring the movement of Bluetooth-enabled devices. To address new challenges caused by such reader-centric Bluetooth data including spatial and temporal distortion, a new route reconstruction framework is proposed to transform Bluetooth readings through a family of distortion suppression strategies such that the transformed data can work well with the Hidden Markov model (HMM) map-matching approach. Extensive experiments are conducted to evaluate different transformation strategies with real-world datasets. The experimental results show that when the algorithm uses the baseline or the proposed transformation strategies, the map matching F1 score can be increased by up to 10% depending on the severity of distortion.","PeriodicalId":233918,"journal":{"name":"Proceedings of the 28th International Conference on Advances in Geographic Information Systems","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127478706","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: 3

Algorithmic Improvement of Crowdsourced Data: Intrinsic Quality Measures, Local Optima, and Consensus 众包数据的算法改进:内在质量度量、局部最优和共识

Proceedings of the 28th International Conference on Advances in Geographic Information Systems Pub Date : 2020-11-03 DOI: 10.1145/3397536.3422260

Thomas C. van Dijk, Norbert Fischer, Bernhard Häussner

引用次数: 2

DiSA

Proceedings of the 28th International Conference on Advances in Geographic Information Systems Pub Date : 2020-11-03 DOI: 10.1145/3397536.3422333

Mengyu Ma, Anran Yang, Ye Wu, Luo Chen, Jun Li, N. Jing

引用次数: 5