3,055 research outputs found
Application of Text Summarization techniques to the Geographical Information Retrieval task
Automatic Text Summarization has been shown to be useful for Natural Language Processing tasks such as Question Answering or Text Classification and other related fields of computer science such as Information Retrieval. Since Geographical Information Retrieval can be considered as an extension of the Information Retrieval field, the generation of summaries could be integrated into these systems by acting as an intermediate stage, with the purpose of reducing the document length. In this manner, the access time for information searching will be improved, while at the same time relevant documents will be also retrieved. Therefore, in this paper we propose the generation of two types of summaries (generic and geographical) applying several compression rates in order to evaluate their effectiveness in the Geographical Information Retrieval task. The evaluation has been carried out using GeoCLEF as evaluation framework and following an Information Retrieval perspective without considering the geo-reranking phase commonly used in these systems. Although single-document summarization has not performed well in general, the slight improvements obtained for some types of the proposed summaries, particularly for those based on geographical information, made us believe that the integration of Text Summarization with Geographical Information Retrieval may be beneficial, and consequently, the experimental set-up developed in this research work serves as a basis for further investigations in this field.This work has been partially funded by the European Commission under the Seventh (FP7-2007-2013) Framework Programme for Research and Technological Development through the FIRST project (FP7-287607). It has also been partially supported by a grant from the Fondo Europeo de Desarrollo Regional (FEDER), projects TEXT-MESS 2.0 (TIN2009-13391-C04-01) and TEXT-COOL 2.0 (TIN2009-13391-C04-02) from the Spanish Government, a Grant from the Valencian Government, project "Desarrollo de Técnicas Inteligentes e Interactivas de Minería de Textos" (PROMETEO/2009/119), and a Grant No. ACOMP/2011/001
Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)
This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio
Spherical similarity explorer for comparative case analysis
Comparative Case Analysis (CCA) is an important tool for criminal investigation and crime theory extraction. It analyzes the commonalities and differences between a collection of crime reports in order to understand crime patterns and identify abnormal cases. A big challenge of CCA is the data processing and exploration. Traditional manual approach can no longer cope with the increasing volume and complexity of the data. In this paper we introduce a novel visual analytics system, Spherical Similarity Explorer (SSE) that automates the data processing process and provides interactive visualizations to support the data exploration. We illustrate the use of the system with uses cases that involve real world application data and evaluate the system with criminal intelligence analysts
A Non-Visual Photo Collection Browser based on Automatically Generated Text Descriptions
This study presents a textual photo collection
browser that automatically and quickly analyses large personal
photo collections and produces textual reports that can be
accessed by blind users using either text-to-speech or Braille
output devices. The textual photo browser exploits recent
advances in image collection analysis and the strategy does not
rely on manual image tagging. The reports produced by the
textual image browser gives the user a gist about where, when
and what the photographer was doing in the form of a story.
Although yet crude, the strategy can give blind users a
valuable overview about the contents of large image collections
and individual images which otherwise are totally inaccessible
without vision
Spherical similarity explorer for comparative case analysis
Comparative Case Analysis (CCA) is an important tool for criminal investigation and crime theory extraction. It analyzes the commonalities and differences between a collection of crime reports in order to understand crime patterns and identify abnormal cases. A big challenge of CCA is the data processing and exploration. Traditional manual approach can no longer cope with the increasing volume and complexity of the data. In this paper we introduce a novel visual analytics system, Spherical Similarity Explorer (SSE) that automates the data processing process and provides interactive visualizations to support the data exploration. We illustrate the use of the system with uses cases that involve real world application data and evaluate the system with criminal intelligence analysts
MusA: Using Indoor Positioning and Navigation to Enhance Cultural Experiences in a museum
In recent years there has been a growing interest into the use of multimedia mobile guides in museum environments. Mobile devices have the capabilities to detect the user context and to provide pieces of information suitable to help visitors discovering and following the logical and emotional connections that develop during the visit. In this scenario, location based services (LBS) currently represent an asset, and the choice of the technology to determine users' position, combined with the definition of methods that can effectively convey information, become key issues in the design process. In this work, we present MusA (Museum Assistant), a general framework for the development of multimedia interactive guides for mobile devices. Its main feature is a vision-based indoor positioning system that allows the provision of several LBS, from way-finding to the contextualized communication of cultural contents, aimed at providing a meaningful exploration of exhibits according to visitors' personal interest and curiosity. Starting from the thorough description of the system architecture, the article presents the implementation of two mobile guides, developed to respectively address adults and children, and discusses the evaluation of the user experience and the visitors' appreciation of these application
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Semantics-Space-Time Cube. A Conceptual Framework for Systematic Analysis of Texts in Space and Time
We propose an approach to analyzing data in which texts are associated with spatial and temporal references with the aim to understand how the text semantics vary over space and time. To represent the semantics, we apply probabilistic topic modeling. After extracting a set of topics and representing the texts by vectors of topic weights, we aggregate the data into a data cube with the dimensions corresponding to the set of topics, the set of spatial locations (e.g., regions), and the time divided into suitable intervals according to the scale of the planned analysis. Each cube cell corresponds to a combination (topic, location, time interval) and contains aggregate measures characterizing the subset of the texts concerning this topic and having the spatial and temporal references within these location and interval. Based on this structure, we systematically describe the space of analysis tasks on exploring the interrelationships among the three heterogeneous information facets, semantics, space, and time. We introduce the operations of projecting and slicing the cube, which are used to decompose complex tasks into simpler subtasks. We then present a design of a visual analytics system intended to support these subtasks. To reduce the complexity of the user interface, we apply the principles of structural, visual, and operational uniformity while respecting the specific properties of each facet. The aggregated data are represented in three parallel views corresponding to the three facets and providing different complementary perspectives on the data. The views have similar look-and-feel to the extent allowed by the facet specifics. Uniform interactive operations applicable to any view support establishing links between the facets. The uniformity principle is also applied in supporting the projecting and slicing operations on the data cube. We evaluate the feasibility and utility of the approach by applying it in two analysis scenarios using geolocated social media data for studying people's reactions to social and natural events of different spatial and temporal scales
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Supporting Story Synthesis: Bridging the Gap between Visual Analytics and Storytelling
Visual analytics usually deals with complex data and uses sophisticated algorithmic, visual, and interactive techniques. Findings of the analysis often need to be communicated to an audience that lacks visual analytics expertise. This requires analysis outcomes to be presented in simpler ways than that are typically used in visual analytics systems. However, not only analytical visualizations may be too complex for target audience but also the information that needs to be presented. Hence, there exists a gap on the path from obtaining analysis findings to communicating them, which involves two aspects: information and display complexity. We propose a general framework where data analysis and result presentation are linked by story synthesis, in which the analyst creates and organizes story contents. Differently, from the previous research, where analytic findings are represented by stored display states, we treat findings as data constructs. In story synthesis, findings are selected, assembled, and arranged in views using meaningful layouts that take into account the structure of information and inherent properties of its components. We propose a workflow for applying the proposed framework in designing visual analytics systems and demonstrate the generality of the approach by applying it to two domains, social media, and movement analysis
Can a map be a geographic information retrieval tool?
This paper is intended to open up discussion on potential co-operation, which
would enable participants restricted by unequal resources and technologies to
participate in a pan-European project. The idea has not yet been fully developed
but the purpose of the project is to allow digital maps to function not
only as geographic resources and educational tools, but to act simultaneously
as an interface to metadata-databases. These would contain de-scriptions of
maps and spatial databases, as well as locational or geo-referenced resources
in books, periodicals, and the Internet
Adventures in Semantic Publishing: Exemplar Semantic Enhancements of a Research Article
Scientific innovation depends on finding, integrating, and re-using the products of
previous research. Here we explore how recent developments in Web technology,
particularly those related to the publication of data and metadata, might assist that
process by providing semantic enhancements to journal articles within the mainstream
process of scholarly journal publishing. We exemplify this by describing semantic
enhancements we have made to a recent biomedical research article taken from
PLoS Neglected Tropical Diseases, providing enrichment to its
content and increased access to datasets within it. These semantic enhancements
include provision of live DOIs and hyperlinks; semantic markup of textual terms, with
links to relevant third-party information resources; interactive figures; a
re-orderable reference list; a document summary containing a study summary, a tag
cloud, and a citation analysis; and two novel types of semantic enrichment: the
first, a Supporting Claims Tooltip to permit “Citations in
Context”, and the second, Tag Trees that bring together semantically
related terms. In addition, we have published downloadable spreadsheets containing
data from within tables and figures, have enriched these with provenance information,
and have demonstrated various types of data fusion (mashups) with results from other
research articles and with Google Maps. We have also published machine-readable RDF
metadata both about the article and about the references it cites, for which we
developed a Citation Typing Ontology, CiTO (http://purl.org/net/cito/). The
enhanced article, which is available at http://dx.doi.org/10.1371/journal.pntd.0000228.x001, presents a
compelling existence proof of the possibilities of semantic publication. We hope the
showcase of examples and ideas it contains, described in this paper, will excite the
imaginations of researchers and publishers, stimulating them to explore the
possibilities of semantic publishing for their own research articles, and thereby
break down present barriers to the discovery and re-use of information within
traditional modes of scholarly communication
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