15 research outputs found
3D Cadastres Best Practices, Chapter 5: Visualization and New Opportunities
This paper proposes a discussion on opportunities offered by 3D visualization to improve the understanding and the analysis of cadastre data. It first introduce the rationale of having 3D visualization functionalities in the context of cadastre applications. Second the publication outline some basic concepts in 3D visualization. This section specially addresses the visualization pipeline as a driven classification schema to understand the steps leading to 3D visualization. In this section is also presented a brief review of current 3D standards and technologies. Next is proposed a summary of progress made in the last years in 3D cadastral visualization. For instance, user’s requirement, data and semiotics, and platforms are highlighted as main actions performed in the development of 3D cadastre visualization. This review could be perceived as an attempt to structure and emphasise the best practices in the domain of 3D cadastre visualization and as an inventory of issues that still need to be tackled. Finally, by providing a review on advances and trends in 3D visualization, the paper initiates a discussion and a critical analysis on the benefit of applying these new developments to cadastre domain. This final section discusses about enhancing 3D techniques as dynamic transparency and cutaway, 3D generalization, 3D visibility model, 3D annotation, 3D data and web platform, augmented reality, immersive virtual environment, 3D gaming, interaction techniques and time
Discovery of Spatiotemporal Event Sequences
Finding frequent patterns plays a vital role in many analytics tasks such as finding itemsets, associations, correlations, and sequences. In recent decades, spatiotemporal frequent pattern mining has emerged with the main goal focused on developing data-driven analysis frameworks for understanding underlying spatial and temporal characteristics in massive datasets. In this thesis, we will focus on discovering spatiotemporal event sequences from large-scale region trajectory datasetes with event annotations. Spatiotemporal event sequences are the series of event types whose trajectory-based instances follow each other in spatiotemporal context. We introduce new data models for storing and processing evolving region trajectories, provide a novel framework for modeling spatiotemporal follow relationships, and present novel spatiotemporal event sequence mining algorithms
Exploring attributes, sequences, and time in Recommender Systems: From classical to Point-of-Interest recommendation
Tesis Doctoral inédita leÃda en la Universidad Autónoma de Madrid, Escuela Politécnica Superior, Departamento de Ingenieria Informática. Fecha de lectura: 08-07-2021Since the emergence of the Internet and the spread of digital communications
throughout the world, the amount of data stored on the Web has been
growing exponentially. In this new digital era, a large number of companies
have emerged with the purpose of ltering the information available on the
web and provide users with interesting items. The algorithms and models
used to recommend these items are called Recommender Systems. These
systems are applied to a large number of domains, from music, books, or
movies to dating or Point-of-Interest (POI), which is an increasingly popular
domain where users receive recommendations of di erent places when
they arrive to a city.
In this thesis, we focus on exploiting the use of contextual information, especially
temporal and sequential data, and apply it in novel ways in both
traditional and Point-of-Interest recommendation. We believe that this type
of information can be used not only for creating new recommendation models
but also for developing new metrics for analyzing the quality of these
recommendations. In one of our rst contributions we propose di erent
metrics, some of them derived from previously existing frameworks, using
this contextual information. Besides, we also propose an intuitive algorithm
that is able to provide recommendations to a target user by exploiting the
last common interactions with other similar users of the system.
At the same time, we conduct a comprehensive review of the algorithms
that have been proposed in the area of POI recommendation between 2011
and 2019, identifying the common characteristics and methodologies used.
Once this classi cation of the algorithms proposed to date is completed, we
design a mechanism to recommend complete routes (not only independent
POIs) to users, making use of reranking techniques. In addition, due to the
great di culty of making recommendations in the POI domain, we propose
the use of data aggregation techniques to use information from di erent
cities to generate POI recommendations in a given target city.
In the experimental work we present our approaches on di erent datasets
belonging to both classical and POI recommendation. The results obtained
in these experiments con rm the usefulness of our recommendation proposals,
in terms of ranking accuracy and other dimensions like novelty, diversity,
and coverage, and the appropriateness of our metrics for analyzing temporal
information and biases in the recommendations producedDesde la aparici on de Internet y la difusi on de las redes de comunicaciones
en todo el mundo, la cantidad de datos almacenados en la red ha crecido
exponencialmente. En esta nueva era digital, han surgido un gran n umero
de empresas con el objetivo de ltrar la informaci on disponible en la red
y ofrecer a los usuarios art culos interesantes. Los algoritmos y modelos
utilizados para recomendar estos art culos reciben el nombre de Sistemas de
Recomendaci on. Estos sistemas se aplican a un gran n umero de dominios,
desde m usica, libros o pel culas hasta las citas o los Puntos de Inter es (POIs,
en ingl es), un dominio cada vez m as popular en el que los usuarios reciben
recomendaciones de diferentes lugares cuando llegan a una ciudad.
En esta tesis, nos centramos en explotar el uso de la informaci on contextual,
especialmente los datos temporales y secuenciales, y aplicarla de forma novedosa
tanto en la recomendaci on cl asica como en la recomendaci on de POIs.
Creemos que este tipo de informaci on puede utilizarse no s olo para crear
nuevos modelos de recomendaci on, sino tambi en para desarrollar nuevas
m etricas para analizar la calidad de estas recomendaciones. En una de
nuestras primeras contribuciones proponemos diferentes m etricas, algunas
derivadas de formulaciones previamente existentes, utilizando esta informaci
on contextual. Adem as, proponemos un algoritmo intuitivo que es
capaz de proporcionar recomendaciones a un usuario objetivo explotando
las ultimas interacciones comunes con otros usuarios similares del sistema.
Al mismo tiempo, realizamos una revisi on exhaustiva de los algoritmos que
se han propuesto en el a mbito de la recomendaci o n de POIs entre 2011 y
2019, identi cando las caracter sticas comunes y las metodolog as utilizadas.
Una vez realizada esta clasi caci on de los algoritmos propuestos hasta la
fecha, dise~namos un mecanismo para recomendar rutas completas (no s olo
POIs independientes) a los usuarios, haciendo uso de t ecnicas de reranking.
Adem as, debido a la gran di cultad de realizar recomendaciones en el
ambito de los POIs, proponemos el uso de t ecnicas de agregaci on de datos
para utilizar la informaci on de diferentes ciudades y generar recomendaciones
de POIs en una determinada ciudad objetivo.
En el trabajo experimental presentamos nuestros m etodos en diferentes
conjuntos de datos tanto de recomendaci on cl asica como de POIs. Los
resultados obtenidos en estos experimentos con rman la utilidad de nuestras
propuestas de recomendaci on en t erminos de precisi on de ranking y de
otras dimensiones como la novedad, la diversidad y la cobertura, y c omo de
apropiadas son nuestras m etricas para analizar la informaci on temporal y
los sesgos en las recomendaciones producida
Urban Informatics
This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity
Urban Informatics
This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity
Urban Informatics
This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity
Remote Sensing in Applications of Geoinformation
Remote sensing, especially from satellites, is a source of invaluable data which can be used to generate synoptic information for virtually all parts of the Earth, including the atmosphere, land, and ocean. In the last few decades, such data have evolved as a basis for accurate information about the Earth, leading to a wealth of geoscientific analysis focusing on diverse applications. Geoinformation systems based on remote sensing are increasingly becoming an integral part of the current information and communication society. The integration of remote sensing and geoinformation essentially involves combining data provided from both, in a consistent and sensible manner. This process has been accelerated by technologically advanced tools and methods for remote sensing data access and integration, paving the way for scientific advances in a broadening range of remote sensing exploitations in applications of geoinformation. This volume hosts original research focusing on the exploitation of remote sensing in applications of geoinformation. The emphasis is on a wide range of applications, such as the mapping of soil nutrients, detection of plastic litter in oceans, urban microclimate, seafloor morphology, urban forest ecosystems, real estate appraisal, inundation mapping, and solar potential analysis
Open Aerial Map, Drones and Archaeology: The implications of using drones to contribute and share aerial data on an open data repository
The purpose of this research is to determine the potential benefits and challenges of volunteered aerial imagery by looking at OpenAerialMap (OAM) and by presenting how a repository like OAM may be applied in archaeological studies. The interviews and survey conducted in this research indicate that the main benefits of OAM are affordability, accessibility, rapid mapping and historic image preservation. Among the key challenges identified are concerns around data quality and privacy. Though most of the images on OAM are of high resolution, there is currently no way to guarantee the quality of images that people share on OAM. Similarly, there are no real safeguards against the misuse the openly available imagery. This is a prominent concern in archaeology, where open aerial images may increase the looting and destruction of heritage sites. Then again, OAM can aid in a number of ways in terms of archaeological research and it may even contribute to citizen engagement in archaeology. The research indicates that OAM is a positive endeavour that makes spatial data more accessible and provides drone users with the ability to engage in citizen science