Effective reorganization and self-indexing of big semantic data

En esta tesis hemos analizado la redundancia estructural que los grafos RDF poseen y propuesto una técnica de preprocesamiento: RDF-Tr, que agrupa, reorganiza y recodifica los triples, tratando dos fuentes de redundancia estructural subyacentes a la naturaleza del esquema RDF. Hemos integrado RDF-Tr en HDT y k2-triples, reduciendo el tamaño que obtienen los compresores originales, superando a las técnicas más prominentes del estado del arte. Hemos denominado HDT++ y k2-triples++ al resultado de aplicar RDF-Tr en cada compresor. En el ámbito de la compresión RDF se utilizan estructuras compactas para construir autoíndices RDF, que proporcionan acceso eficiente a los datos sin descomprimirlos. HDT-FoQ es utilizado para publicar y consumir grandes colecciones de datos RDF. Hemos extendido HDT++, llamándolo iHDT++, para resolver patrones SPARQL, consumiendo menos memoria que HDT-FoQ, a la vez que acelera la resolución de la mayoría de las consultas, mejorando la relación espacio-tiempo del resto de autoíndices.Departamento de Informática (Arquitectura y Tecnología de Computadores, Ciencias de la Computación e Inteligencia Artificial, Lenguajes y Sistemas Informáticos)Doctorado en Informátic

An assessment of the influence of CCAFS' climate data and tools on outcomes achieved 2010-2016

These four volumes comprise an evaluation report commissioned by the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS). The evaluation was undertaken by the independent evaluators Kornelia Rassmann and Tonya Schuetz and supported by the CCAFS internal evaluation team led by Philip Thornton and Laura Cramer. It mainly used Outcome Harvesting (OH) but also elements from Impact Pathway thinking and Contribution Analysis to describe and analyze ‘development outcomes’ that were directly or indirectly influenced by one of three CCAFS’ climate products – the GCM Climate Portal, MarkSimGCM, and the Climate Analogues tool. Volume 1 is the main evaluation report. Volume 2 presents survey results and user perspectives. Volume 3 contains outcome stories. Volume 4 has definitions of terms and the coding book used during the evaluation

Design and Evaluation of Web-Based Economic Indicators: A Big Data Analysis Approach

Tesis por compendio[ES] En la Era Digital, el creciente uso de Internet y de dispositivos digitales está transformando completamente la forma de interactuar en el contexto económico y social. Miles de personas, empresas y organismos públicos utilizan Internet en sus actividades diarias, generando de este modo una enorme cantidad de datos actualizados ("Big Data") accesibles principalmente a través de la World Wide Web (WWW), que se ha convertido en el mayor repositorio de información del mundo. Estas huellas digitales se pueden rastrear y, si se procesan y analizan de manera apropiada, podrían ayudar a monitorizar en tiempo real una infinidad de variables económicas. En este contexto, el objetivo principal de esta tesis doctoral es generar indicadores económicos, basados en datos web, que sean capaces de proveer regularmente de predicciones a corto plazo ("nowcasting") sobre varias actividades empresariales que son fundamentales para el crecimiento y desarrollo de las economías. Concretamente, tres indicadores económicos basados en la web han sido diseñados y evaluados: en primer lugar, un indicador de orientación exportadora, basado en un modelo que predice si una empresa es exportadora; en segundo lugar, un indicador de adopción de comercio electrónico, basado en un modelo que predice si una empresa ofrece la posibilidad de venta online; y en tercer lugar, un indicador de supervivencia empresarial, basado en dos modelos que indican la probabilidad de supervivencia de una empresa y su tasa de riesgo. Para crear estos indicadores, se han descargado una diversidad de datos de sitios web corporativos de forma manual y automática, que posteriormente se han procesado y analizado con técnicas de análisis Big Data. Los resultados muestran que los datos web seleccionados están altamente relacionados con las variables económicas objeto de estudio, y que los indicadores basados en la web que se han diseñado en esta tesis capturan en un alto grado los valores reales de dichas variables económicas, siendo por tanto válidos para su uso por parte del mundo académico, de las empresas y de los decisores políticos. Además, la naturaleza online y digital de los indicadores basados en la web hace posible proveer regularmente y de forma barata de predicciones a corto plazo. Así, estos indicadores son ventajosos con respecto a los indicadores tradicionales. Esta tesis doctoral ha contribuido a generar conocimiento sobre la viabilidad de producir indicadores económicos con datos online procedentes de sitios web corporativos. Los indicadores que se han diseñado pretenden contribuir a la modernización en la producción de estadísticas oficiales, así como ayudar a los decisores políticos y los gerentes de empresas a tomar decisiones informadas más rápidamente.[CA] A l'Era Digital, el creixent ús d'Internet i dels dispositius digitals està transformant completament la forma d'interactuar al context econòmic i social. Milers de persones, empreses i organismes públics utilitzen Internet a les seues activitats diàries, generant d'aquesta forma una enorme quantitat de dades actualitzades ("Big Data") accessibles principalment mitjançant la World Wide Web (WWW), que s'ha convertit en el major repositori d'informació del món. Aquestes empremtes digitals poden rastrejar-se i, si se processen i analitzen de forma apropiada, podrien ajudar a monitoritzar en temps real una infinitat de variables econòmiques. En aquest context, l'objectiu principal d'aquesta tesi doctoral és generar indicadors econòmics, basats en dades web, que siguen capaços de proveïr regularment de prediccions a curt termini ("nowcasting") sobre diverses activitats empresarials que són fonamentals per al creixement i desenvolupament de les economies. Concretament, tres indicadors econòmics basats en la web han sigut dissenyats i avaluats: en primer lloc, un indicador d'orientació exportadora, basat en un model que prediu si una empresa és exportadora; en segon lloc, un indicador d'adopció de comerç electrònic, basat en un model que prediu si una empresa ofereix la possibilitat de venda online; i en tercer lloc, un indicador de supervivència empresarial, basat en dos models que indiquen la probabilitat de supervivència d'una empresa i la seua tasa de risc. Per a crear aquestos indicadors, s'han descarregat una diversitat de dades de llocs web corporatius de forma manual i automàtica, que posteriorment s'han analitzat i processat amb tècniques d'anàlisi Big Data. Els resultats mostren que les dades web seleccionades estan altament relacionades amb les variables econòmiques objecte d'estudi, i que els indicadors basats en la web que s'han dissenyat en aquesta tesi capturen en un alt grau els valors reals d'aquestes variables econòmiques, sent per tant vàlids per al seu ús per part del món acadèmic, de les empreses i dels decisors polítics. A més, la naturalesa online i digital dels indicadors basats en la web fa possible proveïr regularment i de forma barata de prediccions a curt termini. D'aquesta forma, són avantatjosos en comparació als indicadors tradicionals. Aquesta tesi doctoral ha contribuït a generar coneixement sobre la viabilitat de produïr indicadors econòmics amb dades online procedents de llocs web corporatius. Els indicadors que s'han dissenyat pretenen contribuïr a la modernització en la producció d'estadístiques oficials, així com ajudar als decisors polítics i als gerents d'empreses a prendre decisions informades més ràpidament.[EN] In the Digital Era, the increasing use of the Internet and digital devices is completely transforming the way of interacting in the economic and social framework. Myriad individuals, companies and public organizations use the Internet for their daily activities, generating a stream of fresh data ("Big Data") principally accessible through the World Wide Web (WWW), which has become the largest repository of information in the world. These digital footprints can be tracked and, if properly processed and analyzed, could help to monitor in real time a wide range of economic variables. In this context, the main goal of this PhD thesis is to generate economic indicators, based on web data, which are able to provide regular, short-term predictions ("nowcasting") about some business activities that are basic for the growth and development of an economy. Concretely, three web-based economic indicators have been designed and evaluated: first, an indicator of firms' export orientation, which is based on a model that predicts if a firm is an exporter; second, an indicator of firms' engagement in e-commerce, which is based on a model that predicts if a firm offers e-commerce facilities in its website; and third, an indicator of firms' survival, which is based on two models that indicate the probability of survival of a firm and its hazard rate. To build these indicators, a variety of data from corporate websites have been retrieved manually and automatically, and subsequently have been processed and analyzed with Big Data analysis techniques. Results show that the selected web data are highly related to the economic variables under study, and the web-based indicators designed in this thesis are capturing to a great extent their real values, thus being valid for their use by the academia, firms and policy-makers. Additionally, the digital and online nature of web-based indicators makes it possible to provide timely, inexpensive predictions about the economy. This way, they are advantageous with respect to traditional indicators. This PhD thesis has contributed to generating knowledge about the viability of producing economic indicators with data coming from corporate websites. The indicators that have been designed are expected to contribute to the modernization of official statistics and to help in making earlier, more informed decisions to policy-makers and business managers.Blázquez Soriano, MD. (2019). Design and Evaluation of Web-Based Economic Indicators: A Big Data Analysis Approach [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/116836TESISCompendi

Consulting local interests first in planning for a national monument

The research represented in this thesis examines the effectiveness of a community-based participatory approach to a planning and decision-making process, in the context of a proposal to proclaim the San Rafael Swell area of Utah as a national monument. When leaders of Emery County in eastern Utah and the Governor of Utah asked President Bush in January 2002 to consider creating a national monument in the San Rafael Swell area in Emery County, Utah, these officials specifically requested that the consideration be made in a manner that would provide for public participation and openness. President Bush in May 2002 initiated what was to be referred to by the Department of the Interior as the San Rafael Swell Study when he asked Secretary of the Interior Gale Norton to gather information on the Swell\u27s historic and scientific features. The process that was partially implemented by the Department, with input from state and local officials, was a unique decision-making effort; at no time had an administration gone about considering a national monument designation in such a way. Bush assured Utah leaders that no monument would be created without the approval of the local communities. In the end, the process was terminated after a controversial referendum vote in the county. The county that was provided a unique opportunity for input into the presidential decision chose the ballot box over the participatory dialogue. The main objectives of this research are to document and evaluate the San Rafael Swell Study and the context from which it originated. The San Rafael Swell Study, as a public participatory approach to planning and decision-making, is evaluated using a set of criteria that are derived from public participatory planning theory

Comprehensive institutional self-study: for the Middle States Associations of Colleges and Schools, Commission on Higher Education, February 2, 2010

Includes Appendices to the Report

Developing a collaborative MOOC learning environment utilizing video sharing with discussion summarization as added-value

With the fast-growing Massive Open Online Courses (MOOC) community and the increase in the number of Learning Management Systems (LMSs) available online, the amount of shared information is massive. Current LMS - in particular MOOC providers - offer many advanced content delivery techniques: interactive video, active retrieval practices, and quizzes to enhance the pedagogical process. The main knowledge creation assets within MOOCs are encapsulated in other tools such as discussion forums, blogs, and wikis. Although these tools exist as separate entities within the platform, they still follow traditional techniques. We believe these tools need to be fully integrated to the main content and encourage spontaneous collaboration. From my experience with some MOOCs, the amount of collaboration and information-sharing is still overwhelming due to the massive number of participants and the limited range of collaborative tools. However, most of the shared information could be redundant or irrelevant. This information must be processed in order to provide the most concise knowledge. Therefore, we need to summarize this information from the discussions, blogs, and wikis and include the most relevant data in the course content. This thesis addresses this shortcoming by suggesting a new system with two primary components to accomplish this task. In the first component, we link the discussion tools to the main course content. Then, in the second component, we apply Natural Language Processing (NLP) techniques to present a summary of all shared content. We use techniques such as Term Frequency - Inverse Document Frequency (TF-IDF), stemming algorithm, Vector Space Model (VSM), and Cosine Similarity to rank the sentences. We then tune the TF-IDF values and boost the sentence ranks using the main content by delegating the first component’s features. The next step involves choosing the most relevant sentence to build our summary. Finally, we evaluate our result using Recall-Oriented Understudy for Gisting Evaluation (ROUGE) system, which compares our automated summary to human extracted summaries. These results demonstrate that we can achieve high improvement summar y compared to the baseline and other similar techniques

A Software-based Knowledge Management System Using Narrative Texts

Technical and professional communicators have in recent research been challenged to make significant contributions to the field of knowledge management, and to learn or create the new technologies allowing them to do so. The purpose of this dissertation is to make such a combined theoretical and applied contribution from the context of the emerging discipline of Texts and Technology. This dissertation explores the field of knowledge management (KM), particularly its relationship to the related study of artificial intelligence (AI), and then recommends a KM software application based on the principles of narratology and narrative information exchange. The focus of knowledge is shifted from the reductive approach of data and information to a holistic approach of meaning and the way people make sense of complex events as experiences expressed in stories. Such an analysis requires a discussion of the evolution of intelligent systems and narrative theory as well as an examination of existing computerized and non-computerized storytelling systems. After a thorough discussion of these issues, an original software program that is used to collect, analyze, and distribute thematic stories within any hierarchical organization is modeled, exemplified, and explained in detail

Top 10 technologies and their impact on CPA\u27s

https://egrove.olemiss.edu/aicpa_guides/2474/thumbnail.jp