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GeoRich '16: Proceedings of the Third International ACM SIGMOD Workshop on Managing and Mining Enriched Geo-Spatial Data
ACM2016 Proceeding
Publisher:
  • Association for Computing Machinery
  • New York
  • NY
  • United States
Conference:
SIGMOD/PODS'16: International Conference on Management of Data San Francisco California 26 June 2016- 1 July 2016
ISBN:
978-1-4503-4309-1
Published:
26 June 2016
Sponsors:
ESRI, TomTom
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Abstract

The aim of GeoRich is to provide a unique forum for discussing in depth the challenges, opportunities, novel techniques and applications on modeling, managing, searching and mining rich geo-spatial data, in order to fuel scientific research on big spatial data applications beyond the current research frontiers. The workshop is intended to bring together researchers from different fields of data-science and geoinformation-science that deal with the management of spatial and spatio-temporal data, social network data, textual data, multimedia data, semantic data and ontologies, uncertain data and other common types of geo-referenced data. The focus of the third GeoRich workshop is to analyze what has been achieved so far and how to further exploit the enormous potential of this data flood. This workshop brought together researchers from the fields of databases, data-science and geoinformation-science, who independently work on similar problems, but often apply different techniques to solve these problems. Focus of this workshop is to create synergies for databases, data-science and geoinformation-science, by sharing ideas and finding common solutions.

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research-article
Open Access
Taming twisted cubes
Article No.: 1, Pages 1–6https://doi.org/10.1145/2948649.2948650

Spatio-temporal grid data form a core structure in Earth and Space sciences alike. While Array Databases have set out to support this information category they only offer integer indexing, corresponding to equidistant grids. However, often grids in ...

research-article
So far away and yet so close: augmenting toponym disambiguation and similarity with text-based networks
Article No.: 2, Pages 1–6https://doi.org/10.1145/2948649.2948651

Place similarity has a central role in geographic information retrieval and geographic information systems, where spatial proximity is frequently just a poor substitute for semantic relatedness. For applications such as toponym disambiguation, ...

research-article
Public Access
GeoSocialBound: an efficient framework for estimating social POI boundaries using spatio--textual information
Article No.: 3, Pages 1–6https://doi.org/10.1145/2948649.2948652

In this paper, we present a novel framework for estimating social point-of-interest (POI) boundaries, also termed GeoSocialBound, utilizing spatio--textual information based on geo-tagged tweets. We first start by defining a social POI boundary as one ...

research-article
Geodata supported classification of patent applications
Article No.: 4, Pages 1–6https://doi.org/10.1145/2948649.2948653

The automatic classification of patent applications into a particular patent classification system remains a challenge with many practical applications. From a computer science point of view, the task is a multi-label hierarchical classification problem,...

research-article
Geo-fingerprinting social media content
Article No.: 5, Pages 1–6https://doi.org/10.1145/2948649.2948654

With the percentage of Twitter users approaching 20% of the US population by 2019, tweets provide a good sample of the public's sentiment and opinion. Consequently such data has been excessively used in commercial and research efforts. While works have ...

research-article
Dynamically ranked top-k spatial keyword search
Article No.: 6, Pages 1–6https://doi.org/10.1145/2948649.2948655

With the growing data volume and popularity of Web services and Location-Based Services (LBS) new spatio-textual application are emerging. These applications are contributing to a deluge of geo-tagged documents. As a result, top-k spatial keyword ...

research-article
Prediction of user app usage behavior from geo-spatial data
Article No.: 7, Pages 1–6https://doi.org/10.1145/2948649.2948656

In the era of mobile Internet, a vast amount of geo-spatial data allows us to gain further insights into human activities, which is critical for Internet Services Providers (ISP) to provide better personalized services. With the pervasiveness of mobile ...

research-article
An empirical study of workers' behavior in spatial crowdsourcing
Article No.: 8, Pages 1–6https://doi.org/10.1145/2948649.2948657

With the ubiquity of smartphones, spatial crowdsourcing (SC) has emerged as a new paradigm that engages mobile users to perform tasks in the physical world. Thus, various SC techniques have been studied for performance optimization. However, little ...

Contributors
  • Emory University
  • Shenzhen University

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  1. Proceedings of the Third International ACM SIGMOD Workshop on Managing and Mining Enriched Geo-Spatial Data
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      Acceptance Rates

      GeoRich '16 Paper Acceptance Rate 8 of 18 submissions, 44%;
      Overall Acceptance Rate 25 of 50 submissions, 50%
      YearSubmittedAcceptedRate
      GeoRich '209444%
      GeoRich '1710880%
      GeoRich '1618844%
      GeoRich'1513538%
      Overall502550%