ACM Transactions on

Spatial Algorithms and Systems (TSAS)

Latest Articles

Grid-Based Method for GPS Route Analysis for Retrieval

Grids are commonly used as histograms to process spatial data in order to detect frequent patterns, predict destinations, or to infer popular places.... (more)

Measuring the Significance of Spatiotemporal Co-Occurrences

Spatiotemporal co-occurrences are the appearances of spatial and temporal overlap relationships among trajectory-based spatiotemporal instances with... (more)

Efficient Visibility Determination in Urban Scenes Considering Terrain Information

In this article, we introduce a novel occlusion culling method working on the server side to provide real-time navigation on web-based systems.... (more)


ACM Transactions on Spatial Algorithms and Systems (TSAS) is a new scholarly journal that publishes high-quality papers on all aspects of spatial algorithms and systems and closely related disciplines. READ MORE

Call-for-nominations: ACM TSAS has issued a call for nominations for its next editor in chief.  The deadline for submitting nominations is March 31, 2018.

Call-for-papers: ACM TSAS has issued a call for papers for its inaugural issue. Please use manuscriptcentral ( to submit articles, check the status of articles and for reviewing tasks.

Forthcoming Articles
Batch processing of Top-k Spatial-textual Queries

Several indexing techniques have been proposed to efficiently answer top-k spatial-textual queries in the last decade. However, all of these approaches focus on answering one query at a time. In contrast, how to design efficient algorithms that can exploit similarities between incoming queries to improve performance has received little attention. In this paper, we study a series of efficient approaches to batch process multiple top-k spatial-textual queries concurrently. We carefully design a variety of indexing structures for the problem space by exploring the effect of prioritizing spatial and textual properties on system performance. Specifically, we present an efficient traversal method, SF-SEP over an existing space-prioritized index structure. Then, we propose a new space-prioritized index structure, the MIR-Tree to support a filter-and-refine based technique, SF-GRP. To support the processing of text-intensive data, we propose an augmented, inverted indexing structure that can easily be added into existing text search engine architectures, and a novel traversal method for batch processing of the queries. In all of these approaches, the goal is to improve the overall performance by sharing the I/O costs of similar queries. Finally, we demonstrate significant I/O savings in our algorithms over traditional approaches by extensive experiments on three real datasets, and compare how properties of different datasets affect the performance. Many applications in streaming, micro-batching of continuous queries, and privacy-aware search can benefit from this line of work.

Analyzing and Predicting Spatial Crime Distribution Using Crowdsourced and Open Data

Data analytics has a significantly increasing impact on tackling various societal challenges. In this paper, we investigate how information from several heterogeneous and publicly available sources can be used to discover insights and make predictions about the spatial distribution of crime in large urban environments, thus contributing to the safety of citizens. A series of important research questions is addressed. First, we examine how useful different types of data are for the task of crime levels prediction, focusing especially on how prediction accuracy can be improved by combining data from multiple information sources. Then, we look into individual features, aiming to identify and quantify the most important factors. Finally, we drill down to different crime types, elaborating on how the prediction accuracy and the importance of individual features vary across them. Our analysis involves 6 different datasets, from which more than 3,000 features are extracted, filtered, and used to learn models for predicting crime rates across 11 different crime categories. Our results indicate that combining data from multiple information sources can significantly improve prediction accuracy. They also highlight which features affect prediction accuracy the most, as well as for which particular crime categories the predictions are more accurate.

Spatio-temporal Matching for Urban Transportation Applications

In this paper we present a search problem in which mobile agents are searching for static resources. Each agent wants to obtain exactly one resource. Both agents and resources are spatially located on a road network and the movement of the agents is constrained to the road network. This problem applies to various transportation applications including: vehicles (agents) searching for parking (resources) and taxicabs (agents) searching for clients to pick up (resources). In this work, we design search algorithms for such scenarios. We model the problem in different scenarios that vary based on the level of information that is available to the agents. These scenarios vary from: scenarios in which agents have complete information about other agents and resources, to scenarios in which agents only have access to a fraction of the data about the availability of resources (uncertain data). We also propose pricing schemes that incentivize vehicles to search for resources in a way that benefits the system and the environment. Our proposed algorithms were tested in a simulation environment that uses real-world data. We were able to attain up to 40% improvements over other approaches that were tested against our algorithms.


Publication Years 2015-2017
Publication Count 34
Citation Count 24
Available for Download 34
Downloads (6 weeks) 329
Downloads (12 Months) 2392
Downloads (cumulative) 5605
Average downloads per article 165
Average citations per article 1
First Name Last Name Award
Pankaj Agarwal ACM Fellows (2002)
Elisa Bertino ACM Fellows (2003)
Chang-Tien Lu ACM Distinguished Member (2015)
Timoleon Sellis ACM Fellows (2013)
ACM Senior Member (2008)
Cyrus Shahabi ACM Distinguished Member (2009)
Moustafa Amin Youssef ACM Distinguished Member (2015)
Roger Zimmermann ACM Distinguished Member (2017)

First Name Last Name Paper Counts
Dieter Pfoser 3
Lars Kulik 2
Rafal Angryk 2
Petrus Martens 2
Maria Damiani 2
Berkay Aydin 2
Fabio Valdés 1
Wouter Meulemans 1
Mauro Negri 1
Kyle Hickmann 1
Carola Wenk 1
Benedikt Budig 1
Wei Niu 1
Pasi Fränti 1
Alexandros Efentakis 1
Salles Magalhães 1
Pankaj Agarwal 1
Timos Sellis 1
Bettina Speckmann 1
Peter Scheuermann 1
Joël Estephan 1
Joachim Gudmundsson 1
Feng Chen 1
Cyrus Shahabi 1
Hitoshi Shimizu 1
Wangchien Lee 1
Juan Banda 1
Karthik Pillai 1
Stylianos Sideridis 1
Alex Beutel 1
Yi Yu 1
Preeti Goel 1
Sara Migliorini 1
Yuan Long 1
Weishinn Ku 1
Chung Kuo 1
Martin Nöllenburg 1
Dimitrios Skoutas 1
Tomoharu Iwata 1
Naonori Ueda 1
Nikos Pelekis 1
Elisa Bertino 1
Sadao Obana 1
Karine Zeitouni 1
André Van Renssen 1
Michael Horton 1
Shanyun Teng 1
Liang Zhao 1
Denian Yang 1
Claudio Silvestri 1
Marcus Andrade 1
Suhua Tang 1
Janne Kovanen 1
Mohammed Ali 1
Sarana Nutanong 1
Thomas Van Dijk 1
Leyla Kazemi 1
Mark Mckennney 1
Andreas Gemsa 1
Jan Haunert 1
Futoshi Naya 1
Daichi Amagata 1
Takahiro Hara 1
M Robles-Ortega 1
Thomas Mølhave 1
Chaulio Ferreira 1
Georgios Skoumas 1
Ralf Güting 1
Kotagiri Ramamohanarao 1
Egemen Tanin 1
Giuseppe Pelagatti 1
Heba Aly 1
Moustafa Youssef 1
Roger Frye 1
Alexander Wolff 1
Hien To 1
Sophia Karagiorgou 1
Lidia Ortega 1
Huiju Hung 1
Christodoulos Efstathiades 1
Dustin Kempton 1
Gabriel Ghinita 1
Dai That 1
Anas Basalamah 1
Sanjay Chawla 1
Kunta Chuang 1
Mahmuda Ahmed 1
Brittany Fasy 1
Sanjay Purushotham 1
Changtien Lu 1
Naren Ramakrishnan 1
Panagiotis Tampakis 1
Anastasios Kyrillidis 1
Roger Zimmermann 1
Iulian Popa 1
Kevin Buchin 1
Tapani Sarjakoski 1
Alberto Belussi 1
Xiaolin Hu 1
James Caverlee 1
Zhijiao Liu 1
Radu Mariescu-Istodor 1
Ahmet Küçük 1
Francisco Feito 1
Yannis Theodoridis 1
Wm Franklin 1

Affiliation Paper Counts
Umm Al Qura University 1
University of Massachusetts Boston 1
Bangladesh University of Engineering and Technology 1
Montana State University - Bozeman 1
Northwestern University 1
Duke University 1
Purdue University 1
Osnabruck University 1
Swinburne University of Technology 1
Hamad bin Khalifa University 1
State University of New York at Albany 1
Auburn University 1
Carnegie Mellon University 1
Microsoft Corporation 1
Stanford University 1
University of Texas at Austin 1
Ca' Foscari University of Venice 1
City University London 1
City University of Hong Kong 1
Rensselaer Polytechnic Institute 1
University of Texas at San Antonio 1
Academia Sinica Taiwan 1
National University of Singapore 1
University of Maryland 1
University of Hagen 2
National Cheng Kung University 2
Southern Illinois University at Edwardsville 2
Pennsylvania State University 2
National Technical University of Athens 2
Athena Research and Innovation Center in Information, Communication and Knowledge Technologies 2
University of Eastern Finland 2
Karlsruhe Institute of Technology 2
Eindhoven University of Technology 2
University of Electro-Communications 2
University of Verona 2
University of Milan 2
Research Organization of Information and Systems National Institute of Informatics 2
Virginia Tech 2
Osaka University 2
Politecnico di Milano 2
Tulane University 3
Universite de Versailles Saint-Quentin-en-Yvelines 3
Universidad de Jaen 3
University of Wurzburg 3
University of Sydney 3
Federal University of Vicosa 3
Texas A and M University System 3
Nippon Telegraph and Telephone Corporation 4
George Mason University 4
University of Southern California 4
University of Piraeus 4
University of Melbourne 5
Georgia State University 10

ACM Transactions on Spatial Algorithms and Systems (TSAS)

Volume 3 Issue 3, November 2017
Volume 3 Issue 2, August 2017 SIGSPATIAL Paper and Regular Papers
Volume 3 Issue 1, May 2017 Regular Papers and SIGSPATIAL Paper

Volume 2 Issue 4, November 2016 Regular Papers and SIGSPATIAL Paper
Volume 2 Issue 3, October 2016
Volume 2 Issue 2, July 2016 Invited Papers from ACM SIGSPATIAL
Volume 2 Issue 1, April 2016

Volume 1 Issue 2, November 2015
Volume 1 Issue 1, August 2015 Inaugural Issue
All ACM Journals | See Full Journal Index

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