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2017 Proceeding- Program Chairs:
- Panagiotis Bouros,
- Mohamed Sarwat
Both the current trends in technology such as smart phones, general mobile devices, stationary sensors and satellites, as well as a new user mentality of utilizing this technology to voluntarily share information, produce a huge flood of geo-spatial data enriched by multiple types of information or contexts, such as social, text, multimedia data and scientific measurements. This data flood provides a tremendous potential of discovering new and useful knowledge. The novel research challenge is to search and mine this wealth of multi-enriched geo-spatial data. The aim of the GeoRich workshop 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. The focus of the fourth installment of GeoRich is to analyze what has been achieved so far and how to further exploit the enormous potential of this data flood. Its ultimate goal is to develop a general framework of methods for searching and mining enriched geo-spatial data in order to fuel an advanced analysis of big data applications beyond the current research frontiers. This year's workshop brought together researchers from different fields of databases, data-science and geo-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. In total, GeoRich 2017 had a total of 10 research paper submissions out of which 8 research papers have been accepted for presentation.
Proceeding Downloads
A lightweight approach to explore, enrich and use data with a geospatial dimension with semantic web technologies
The concept of "location" provides one a useful dimension to explore, align, combine, and analyze data. Though one can rely on bespoke GIS systems to conduct their data analyses, we aim to investigate the feasibility of using Semantic Web technologies ...
Extracting visited points of interest from vehicle trajectories
Identifying visited points of interest (PoIs) from vehicle trajectories remains an open problem that is difficult due to vehicles parking often at some distance from the visited PoI and due to some regions having a high PoI density. We propose a visited ...
Using contexts and constraints for improved geotagging of human trafficking webpages
Extracting geographical tags from webpages is a well-motiva-ted application in many domains. In illicit domains with unusual language models, like human trafficking, extracting geotags with both high precision and recall is a challenging problem. In ...
A large-scale spatio-temporal data analytics system for wildfire risk management
Wildfires have been a significant concern for communities and fire response agencies in many countries. Hence, it is critical to be able to predict the fire risk in a timely and accurate manner and at granular level. However, this requires accessing and ...
Secure sharing of geospatial wildlife data
Modern tracking technologies enables new ways for data mining in the wild. It allows wildlife monitoring centers to permanently collect geospatial data in a non-intrusive manner in real-time and at low cost. Unfortunately, wildlife data is exposed to ...
Spatio-temporal prediction of social connections
It is long known that a user's mobility pattern can be affected by his social connections. Users tend to visit same locations visited by their friends. In this paper we investigate the inverse problem: How does a set of user trajectories reflect their ...
Finding suitable places for live campaigns using location-based services
In the recent years, the idea of reaching customers through human experience has triggered a new marketing strategy known as live campaigns. We can expect that live campaigns will become more pervasive and profitable, but not before addressing key ...
Experimental evaluation of selectivity estimation on big spatial data
With the tremendous volume of spatial datasets, there is an increasing need to process and analyze spatial data. One of the fundamental spatial queries is the selectivity estimation problem where users want to quickly estimate the total number of ...
Index Terms
- Proceedings of the Fourth International ACM Workshop on Managing and Mining Enriched Geo-Spatial Data
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Acceptance Rates
| Year | Submitted | Accepted | Rate |
|---|---|---|---|
| GeoRich '20 | 9 | 4 | 44% |
| GeoRich '17 | 10 | 8 | 80% |
| GeoRich '16 | 18 | 8 | 44% |
| GeoRich'15 | 13 | 5 | 38% |
| Overall | 50 | 25 | 50% |