101,727 research outputs found
A new splitting-based displacement prediction approach for location-based services
In location-based services (LBSs), the service is provided based on the users' locations through location determination and mobility realization. Several location prediction models have been proposed to enhance and increase the relevance of the information retrieved by users of mobile information systems, but none of them studied the relationship between accuracy rate of prediction and the performance of the model in terms of consuming resources and constraints of mobile devices. Most of the current location prediction research is focused on generalized location models, where the geographic extent is divided into regular-shape cells. These models are not suitable for certain LBSs where the objectives are to compute and present on-road services. One such technique is the Prediction Location Model (PLM), which deals with inner cell structure. The PLM technique suffers from memory usage and poor accuracy. The main goal of this paper is to propose a new path prediction technique for Location-Based Services. The new approach is competitive and more efficient compared to PLM regarding measurements such as accuracy rate of location prediction and memory usage
Technology Integration around the Geographic Information: A State of the Art
One of the elements that have popularized and facilitated the use of geographical information on a variety of computational applications has been the use of Web maps; this has opened new research challenges on different subjects, from locating places and people, the study of social behavior or the analyzing of the hidden structures of the terms used in a natural language query used for locating a place. However, the use of geographic information under technological features is not new, instead it has been part of a development and technological integration process. This paper presents a state of the art review about the application of geographic information under different approaches: its use on location based services, the collaborative user participation on it, its contextual-awareness, its use in the Semantic Web and the challenges of its use in natural languge queries. Finally, a prototype that integrates most of these areas is presented
Geo-Spotting: Mining Online Location-based Services for Optimal Retail Store Placement
The problem of identifying the optimal location for a new retail store has
been the focus of past research, especially in the field of land economy, due
to its importance in the success of a business. Traditional approaches to the
problem have factored in demographics, revenue and aggregated human flow
statistics from nearby or remote areas. However, the acquisition of relevant
data is usually expensive. With the growth of location-based social networks,
fine grained data describing user mobility and popularity of places has
recently become attainable.
In this paper we study the predictive power of various machine learning
features on the popularity of retail stores in the city through the use of a
dataset collected from Foursquare in New York. The features we mine are based
on two general signals: geographic, where features are formulated according to
the types and density of nearby places, and user mobility, which includes
transitions between venues or the incoming flow of mobile users from distant
areas. Our evaluation suggests that the best performing features are common
across the three different commercial chains considered in the analysis,
although variations may exist too, as explained by heterogeneities in the way
retail facilities attract users. We also show that performance improves
significantly when combining multiple features in supervised learning
algorithms, suggesting that the retail success of a business may depend on
multiple factors.Comment: Proceedings of the 19th ACM SIGKDD international conference on
Knowledge discovery and data mining, Chicago, 2013, Pages 793-80
Multi-dimensional modelling for the national mapping agency: a discussion of initial ideas, considerations, and challenges
The Ordnance Survey, the National Mapping Agency (NMA) for Great Britain, has recently
begun to research the possible extension of its 2-dimensional geographic information into a
multi-dimensional environment. Such a move creates a number of data creation and storage
issues which the NMA must consider. Many of these issues are highly relevant to all NMAâs
and their customers alike, and are presented and explored here.
This paper offers a discussion of initial considerations which NMAâs face in the creation of
multi-dimensional datasets. Such issues include assessing which objects should be mapped in
3 dimensions by a National Mapping Agency, what should be sensibly represented
dynamically, and whether resolution of multi-dimensional models should change over space.
This paper also offers some preliminary suggestions for the optimal creation method for any
future enhanced national height model for the Ordnance Survey. This discussion includes
examples of problem areas and issues in both the extraction of 3-D data and in the
topological reconstruction of such. 3-D feature extraction is not a new problem. However, the
degree of automation which may be achieved and the suitability of current techniques for
NMAâs remains a largely unchartered research area, which this research aims to tackle.
The issues presented in this paper require immediate research, and if solved adequately
would mark a cartographic paradigm shift in the communication of geographic information â
and could signify the beginning of the way in which NMAâs both present and interact with
their customers in the future
Smart Geographic object: Toward a new understanding of GIS Technology in Ubiquitous Computing
One of the fundamental aspects of ubiquitous computing is the instrumentation
of the real world by smart devices. This instrumentation constitutes an
opportunity to rethink the interactions between human beings and their
environment on the one hand, and between the components of this environment on
the other. In this paper we discuss what this understanding of ubiquitous
computing can bring to geographic science and particularly to GIS technology.
Our main idea is the instrumentation of the geographic environment through the
instrumentation of geographic objects composing it. And then investigate how
this instrumentation can meet the current limitations of GIS technology, and
offers a new stage of rapprochement between the earth and its abstraction. As
result, the current research work proposes a new concept we named Smart
Geographic Object SGO. The latter is a convergence point between the smart
objects and geographic objects, two concepts appertaining respectively to
From Sensor to Observation Web with Environmental Enablers in the Future Internet
This paper outlines the grand challenges in global sustainability research and the objectives of the FP7 Future Internet PPP program within the Digital Agenda for Europe. Large user communities are generating significant amounts of valuable environmental observations at local and regional scales using the devices and services of the Future Internet. These communitiesâ environmental observations represent a wealth of information which is currently hardly used or used only in isolation and therefore in need of integration with other information sources. Indeed, this very integration will lead to a paradigm shift from a mere Sensor Web to an Observation Web with semantically enriched content emanating from sensors, environmental simulations and citizens. The paper also describes the research challenges to realize the Observation Web and the associated environmental enablers for the Future Internet. Such an environmental enabler could for instance be an electronic sensing device, a web-service application, or even a social networking group affording or facilitating the capability of the Future Internet applications to consume, produce, and use environmental observations in cross-domain applications. The term ?envirofied? Future Internet is coined to describe this overall target that forms a cornerstone of work in the Environmental Usage Area within the Future Internet PPP program. Relevant trends described in the paper are the usage of ubiquitous sensors (anywhere), the provision and generation of information by citizens, and the convergence of real and virtual realities to convey understanding of environmental observations. The paper addresses the technical challenges in the Environmental Usage Area and the need for designing multi-style service oriented architecture. Key topics are the mapping of requirements to capabilities, providing scalability and robustness with implementing context aware information retrieval. Another essential research topic is handling data fusion and model based computation, and the related propagation of information uncertainty. Approaches to security, standardization and harmonization, all essential for sustainable solutions, are summarized from the perspective of the Environmental Usage Area. The paper concludes with an overview of emerging, high impact applications in the environmental areas concerning land ecosystems (biodiversity), air quality (atmospheric conditions) and water ecosystems (marine asset management)
Focussed palmtop information access combining starfield displays and profile-based recommendations
This paper presents two palmtop applications: Taeneb CityGuide and Taeneb ConferenceGuide. Both applications are centred around Starfield displays on palmtop computers - this provides fast, dynamic access to information on a small platform. The paper describes the applications focussing on this novel palmtop information access method and on the user-profiling aspect of the CityGuide, where restaurants are recommended to users based on both the match of restaurant type to the users' observed previous interactions and the rating given by reviewers with similar observed preferences
A Survey of Volunteered Open Geo-Knowledge Bases in the Semantic Web
Over the past decade, rapid advances in web technologies, coupled with
innovative models of spatial data collection and consumption, have generated a
robust growth in geo-referenced information, resulting in spatial information
overload. Increasing 'geographic intelligence' in traditional text-based
information retrieval has become a prominent approach to respond to this issue
and to fulfill users' spatial information needs. Numerous efforts in the
Semantic Geospatial Web, Volunteered Geographic Information (VGI), and the
Linking Open Data initiative have converged in a constellation of open
knowledge bases, freely available online. In this article, we survey these open
knowledge bases, focusing on their geospatial dimension. Particular attention
is devoted to the crucial issue of the quality of geo-knowledge bases, as well
as of crowdsourced data. A new knowledge base, the OpenStreetMap Semantic
Network, is outlined as our contribution to this area. Research directions in
information integration and Geographic Information Retrieval (GIR) are then
reviewed, with a critical discussion of their current limitations and future
prospects
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