Lecture Notes by Mustafa Jarrar at Birzeit University, Palestine.
See the course webpage at: http://jarrar-courses.blogspot.com/2014/01/web-data-management.html
and http://www.jarrar.info
you may also watch this lecture at: http://www.youtube.com/watch?v=rH9mksypcNw
The lecture covers Data Integration and Fusion
Lecture Notes by Mustafa Jarrar at Birzeit University, Palestine.
See the course webpage at: http://jarrar-courses.blogspot.com/2014/01/data-schema-integration.html and http://www.jarrar.info
you may also watch this lecture at: http://www.youtube.com/watch?v=VJtF_7ptln4
The lecture covers:
- Challenges of Data Schema Integration
- Framework for Schema Integration
- Schema Transformation
- Reverse Engineering
Mail volumes have decreased dramatically since the proliferation of the internet. Revenues are going down and costs are going up. Postal organizations are trying to cut costs, but unfortunately the cost savings alone are most likely not enough to turn things around. Postal providers need to act. They have to adapt their business and conduct an innovation strategy. This has to happen in traditional mail services, but also in finding new growth drivers in order to differentiate themselves to survive. Discover what are the monetization challenges and revenue management process renovations associated with this needed transformation.
Lecture Notes by Mustafa Jarrar at Birzeit University, Palestine.
See the course webpage at: http://jarrar-courses.blogspot.com/2014/01/web-data-management.html
and http://www.jarrar.info
you may also watch this lecture at: http://www.youtube.com/watch?v=rH9mksypcNw
The lecture covers Data Integration and Fusion
Lecture Notes by Mustafa Jarrar at Birzeit University, Palestine.
See the course webpage at: http://jarrar-courses.blogspot.com/2014/01/data-schema-integration.html and http://www.jarrar.info
you may also watch this lecture at: http://www.youtube.com/watch?v=VJtF_7ptln4
The lecture covers:
- Challenges of Data Schema Integration
- Framework for Schema Integration
- Schema Transformation
- Reverse Engineering
Mail volumes have decreased dramatically since the proliferation of the internet. Revenues are going down and costs are going up. Postal organizations are trying to cut costs, but unfortunately the cost savings alone are most likely not enough to turn things around. Postal providers need to act. They have to adapt their business and conduct an innovation strategy. This has to happen in traditional mail services, but also in finding new growth drivers in order to differentiate themselves to survive. Discover what are the monetization challenges and revenue management process renovations associated with this needed transformation.
We introduce a new mobile system framework, SenSec, which uses passive sensory data to ensure the security of applications and data on mobile devices.
SenSec constantly collects sensory data from accelerometers, gyroscopes and magnetometers and constructs the gesture model of how a user uses the device.
SenSec calculates the sureness that the mobile device is being used by its owner.
Based on the sureness score, mobile devices can dynamically request the user to provide active authentication (such as a strong password), or disable certain features of the mobile devices to protect user's privacy and information security.
In this paper, we model such gesture patterns through a continuous n-gram language model using a set of features constructed from these sensors. We built mobile application prototype based on this model and use it to perform both user classification and user authentication experiments. User studies show that SenSec can achieve 75 accuracy in identifying the users and 71.3 accuracy in detecting the non-owners with only 13.1 false alarms.
Using Ontological Contexts to Assess the Relevance of Statements in Ontolâ¦fzablith
This talk is in the Semantic Web research field. It is about discussing how to evaluate the relevance of statements by comparing the contexts derived from online ontologies, to the ontology under evolution.
It includes an evaluation and comparison of 2 approaches: an overlap-based approach and pattern-based approach, showing how patterns outperform the base techniques.
It also includes the integration of the work in the ontology evolution tool Evolva.
Activity recognition based on a multi-sensor meta-classifierOresti Banos
Ensuring ubiquity, robustness and continuity of monitoring
is of key importance in activity recognition. To that end, multiple sensor congurations and fusion techniques are ever more used. In this paper we present a multi-sensor meta-classier that aggregates the knowledge of several sensor-based decision entities to provide a unique and reliable activity classication. This model introduces a new weighting scheme which improves the rating of the impact that each entity has on the decision fusion process. Sensitivity and specicity are particularly considered as insertion and rejection weighting metrics instead of the overall accuracy classication performance proposed in a previous work. For the sake of comparison, both new and previous weighting models together with feature fusion models are tested on an extensive activity recognition
benchmark dataset. The results demonstrate that the new weighting scheme enhances the decision aggregation thus leading to an improved recognition system.
This presentation illustrates part of the work described in the following articles:
* Banos, O., Damas, M., Pomares, H., Rojas, F., Delgado-Marquez, B. & Valenzuela, O.
Human activity recognition based on a sensor weighting hierarchical classifier.
Soft Computing - A Fusion of Foundations, Methodologies and Applications, Springer Berlin / Heidelberg, vol. 17, pp. 333-343 (2013)
* Banos, O., Damas, M., Pomares, H., Rojas, I.: Activity recognition based on a multi-sensor meta-classifier. In: Proceedings of the 2013 International Work Conference on Neural Networks (IWANN 2013), Tenerife, Spain, June 12-14, (2013)
Pattern matching against event streams is a new paradigm of processing continuously arriving events with the goal of identifying meaningful patterns (complex events). An issue arises when some events get delayed due to, e.g., network latencies or sensor and machine failures. In this work we propose a novel technique for processing out-of-order events without artificial delays. We present the design of an out-of-order event processor, and a general low-level garbage collector; both implemented in ETALIS system.
"System Modeling" Course - talks are on
Event Relationship Graphs and Petri Nets for dynamic event driven system modeling
at Center for Artificial Intelligence and Robotics (CAIR), DRDO, at Bengaluru, 21st January 2016.
Ouvidoria de Balcão vs Ouvidoria Digital: Desafios na Era Big DataRommel Carvalho
Apresentação realizada no dia 14/03/2017 por Rommel N. Carvalho na Semana de Ouvidoria e Acesso à Informação de 2017, organizada pela CGU.
YouTube: https://youtu.be/vNMtULu5X1c?t=3h20m24s
Como transformar servidores em cientistas de dados e diminuir a distância ent...Rommel Carvalho
Palestra ministrada pelo Dr. Rommel Novaes Carvalho, Coordenador-Geral do Observatório da Despesa Pública e Professor do Mestrado Profissional em Computação Aplicada da UnB.
Evento: Brasil 100% Digital: Integração e transparência a serviço da sociedade
Website: http://www.brasildigital.gov.br/
Data: 10/11/2016
Vídeo: https://www.youtube.com/watch?v=3WYQlPR-RLw&feature=youtu.be&t=2h4m44s
More Related Content
Similar to AFCEA 2010 - High Level Fusion and Predictive Situational Awareness with Probabilistic Ontologies
We introduce a new mobile system framework, SenSec, which uses passive sensory data to ensure the security of applications and data on mobile devices.
SenSec constantly collects sensory data from accelerometers, gyroscopes and magnetometers and constructs the gesture model of how a user uses the device.
SenSec calculates the sureness that the mobile device is being used by its owner.
Based on the sureness score, mobile devices can dynamically request the user to provide active authentication (such as a strong password), or disable certain features of the mobile devices to protect user's privacy and information security.
In this paper, we model such gesture patterns through a continuous n-gram language model using a set of features constructed from these sensors. We built mobile application prototype based on this model and use it to perform both user classification and user authentication experiments. User studies show that SenSec can achieve 75 accuracy in identifying the users and 71.3 accuracy in detecting the non-owners with only 13.1 false alarms.
Using Ontological Contexts to Assess the Relevance of Statements in Ontolâ¦fzablith
This talk is in the Semantic Web research field. It is about discussing how to evaluate the relevance of statements by comparing the contexts derived from online ontologies, to the ontology under evolution.
It includes an evaluation and comparison of 2 approaches: an overlap-based approach and pattern-based approach, showing how patterns outperform the base techniques.
It also includes the integration of the work in the ontology evolution tool Evolva.
Activity recognition based on a multi-sensor meta-classifierOresti Banos
Ensuring ubiquity, robustness and continuity of monitoring
is of key importance in activity recognition. To that end, multiple sensor congurations and fusion techniques are ever more used. In this paper we present a multi-sensor meta-classier that aggregates the knowledge of several sensor-based decision entities to provide a unique and reliable activity classication. This model introduces a new weighting scheme which improves the rating of the impact that each entity has on the decision fusion process. Sensitivity and specicity are particularly considered as insertion and rejection weighting metrics instead of the overall accuracy classication performance proposed in a previous work. For the sake of comparison, both new and previous weighting models together with feature fusion models are tested on an extensive activity recognition
benchmark dataset. The results demonstrate that the new weighting scheme enhances the decision aggregation thus leading to an improved recognition system.
This presentation illustrates part of the work described in the following articles:
* Banos, O., Damas, M., Pomares, H., Rojas, F., Delgado-Marquez, B. & Valenzuela, O.
Human activity recognition based on a sensor weighting hierarchical classifier.
Soft Computing - A Fusion of Foundations, Methodologies and Applications, Springer Berlin / Heidelberg, vol. 17, pp. 333-343 (2013)
* Banos, O., Damas, M., Pomares, H., Rojas, I.: Activity recognition based on a multi-sensor meta-classifier. In: Proceedings of the 2013 International Work Conference on Neural Networks (IWANN 2013), Tenerife, Spain, June 12-14, (2013)
Pattern matching against event streams is a new paradigm of processing continuously arriving events with the goal of identifying meaningful patterns (complex events). An issue arises when some events get delayed due to, e.g., network latencies or sensor and machine failures. In this work we propose a novel technique for processing out-of-order events without artificial delays. We present the design of an out-of-order event processor, and a general low-level garbage collector; both implemented in ETALIS system.
"System Modeling" Course - talks are on
Event Relationship Graphs and Petri Nets for dynamic event driven system modeling
at Center for Artificial Intelligence and Robotics (CAIR), DRDO, at Bengaluru, 21st January 2016.
Ouvidoria de Balcão vs Ouvidoria Digital: Desafios na Era Big DataRommel Carvalho
Apresentação realizada no dia 14/03/2017 por Rommel N. Carvalho na Semana de Ouvidoria e Acesso à Informação de 2017, organizada pela CGU.
YouTube: https://youtu.be/vNMtULu5X1c?t=3h20m24s
Como transformar servidores em cientistas de dados e diminuir a distância ent...Rommel Carvalho
Palestra ministrada pelo Dr. Rommel Novaes Carvalho, Coordenador-Geral do Observatório da Despesa Pública e Professor do Mestrado Profissional em Computação Aplicada da UnB.
Evento: Brasil 100% Digital: Integração e transparência a serviço da sociedade
Website: http://www.brasildigital.gov.br/
Data: 10/11/2016
Vídeo: https://www.youtube.com/watch?v=3WYQlPR-RLw&feature=youtu.be&t=2h4m44s
Proposta de Modelo de Classificação de Riscos de Contratos PúblicosRommel Carvalho
Palestra ministrada pelo Leonardo Jorge Sales no 2o Seminário sobre Análise de Dados na Administração Pública @ http://www.brasildigital.gov.br/
Resumo: Contratos públicos são o meio pelo qual os recursos do governo são aplicados e as políticas públicas são desenvolvidas. No Brasil, respondem por mais de 19% do PIB. Considerando o desafio das instituições de controle governamental brasileiras de garantir eficiência e regularidade nesses processos, propõe-se neste trabalho a utilização de modelos econométricos para seleção de casos para auditoria. São desenvolvidas três abordagens, sendo a primeira a estruturação de um modelo de classificação de risco do fornecedor (empresa contratada), baseado em características como sua capacidade operacional e histórico de contratações anteriores, e a segunda um modelo mais amplo de classificação do risco dos contratos, com base nas características do próprio fornecedor, do contrato e da licitação que o antecedeu. Esses dois modelos usarão a técnica de regressão logística para a estimação dos parâmetros. A terceira abordagem propõe um modelo de decisão multicritério para seleção final de contratos a serem auditados considerando os scores de risco criados juntamente com os aspectos logísticos mais relevantes para a execução das fiscalizações. O modelo multicritério utilizará a técnica de Analytic Hierarchy Process (AHP).
Palestrante: Leonardo Jorge Sales - Ministério da Transparência, Fiscalização e Controle
Currículo: Possui graduação em Administração pela Universidade Federal de Pernambuco e Pós-Graduação em Auditoria Governamental pelo Instituto Serzedello Correa - ISC, do Tribunal de Contas da União e Mestrado em Economia pela Universidade de Brasília (UNB). Tem experiência profissional nas áreas de controle governamental, auditoria interna e análise de dados aplicada à detecção de fraudes e ao desenvolvimento de indicadores de risco e qualidade. Trabalha atualmente no Ministério da Transparência, Fiscalização e Controle (MTFC), exercendo suas atividades na Diretoria de Pesquisas e Informações Estratégicas.
Categorização de achados em auditorias de TI com modelos supervisionados e nã...Rommel Carvalho
Palestra ministrada pela Patrícia Maia no 2o Seminário sobre Análise de Dados na Administração Pública @ http://www.brasildigital.gov.br/
Resumo: O trabalho consistiu na aplicação de técnicas de mineração de textos para identificação dos principais assuntos abordados nas auditorias dos últimos cinco anos. Foram utilizadas duas abordagens: a abordagem supervisionada aplicando classificação de textos com o algoritmo Random Forest e a abordagem não supervisionada através da técnica de modelagem de tópicos Latent Dirichlet Allocation (LDA). O projeto piloto foi validado com as constatações de TI e está agora sendo estendido a constatações relacionadas a outros temas. O objetivo é permitir catalogar o histórico de constatações emitidas e categorizar automaticamente novos registros. Com isso, os servidores poderão recuperar situações semelhantes para aplicação em novos trabalhos ou, ainda, tratar problemas recorrentes de forma estruturante. Além disso a mesma lógica pode ser usada para gerar conhecimento a partir de outros tipos de texto: pedidos com base na Lei de Acesso à Informações, manifestações do e-OUV, processos analisados pela CRG, notícias de interesse do órgão, etc.
Palestrante: Patrícia Maia - Ministério da Transparência, Fiscalização e Controle
Currículo: Possui mestrado em Computação Aplicada pela Universidade de Brasília (UNB), especialização em Modelagem de Processos e Engenharia de Requisitos pela Universidade Federal do Rio Grande do SUL (UFRGS) e graduação em Tecnologia da Informação. Tem experiência profissional nas áreas de mineração de textos, ETL, banco de dados e controle governamental. Trabalha atualmente no Ministério da Transparência, Fiscalização e Controle (MTFC), exercendo suas atividades na Diretoria de Pesquisas e Informações Estratégicas.
Mapeamento de risco de corrupção na administração pública federalRommel Carvalho
Palestra ministrada pelo Dr. Rommel Novaes Carvalho no 2o Seminário sobre Análise de Dados na Administração Pública @ http://www.brasildigital.gov.br/
Resumo: O Ministério da Transparência (CGU) tem, entre suas atribuições, investigar possíveis irregularidades cometidas por servidores públicos federais. Nesse contexto, nasceu o projeto MARA, que aplica mineração de dados para gerar modelos preditivos com a finalidade de avaliar risco de corrupção de servidores públicos federais a partir de diversas bases de dados governamentais. Esse trabalho possibilitou o uso mais eficiente e eficaz de recursos e pessoal da CGU; com impacto nacional; incremento na metodologia de priorização de trabalhos; e o fortalecimento do controle prévio.
Palestrante: Rommel Novaes Carvalho - Ministério da Transparência, Fiscalização e Controle
Currículo: Coordenador-Geral do Observatório da Despesa Pública (ODP), lidera equipe de aproximadamente 15 Cientistas de Dados responsáveis por monitorar gastos públicos, identificar fraudes e combater a corrupção. Além disso, é Professor do Mestrado Profissional em Computação Aplicada da UnB.
Palestra realizada pelo Coordenador-Geral do Observatório da Despesa Pública (ODP) do Ministério da Transparência, Fiscalização e Controle (MTFC) no evento Ciência de Dados e Sociedade organizado pelo Instituto Brasileiro de Pesquisa e Análise de Dados. (IBPAD).
Evento: http://www.eventbrite.com.br/e/seminarios-ibpad-ciencia-de-dados-e-sociedade-tickets-25481490825
Aplicação de técnicas de mineração de textos para classificação automática de...Rommel Carvalho
O uso de classificação automática de textos tem se tornado cada vez mais comum nos últimos anos. Contudo, ao se trabalhar com classificação em larga escala, a complexidade aumenta consideravelmente. Foi realizado um estudo de caso, aplicado à triagem de denúncias na Controladoria Geral da União, utilizando uma grande quantidade de categorias a serem classificadas. A solução proposta empregou aprendizagem de máquina e classificação multilabel. Essas técnicas tiveram como objetivo a construção de um modelo capaz de solucionar adversidades inerentes a este contexto, apresentando ganhos significativos
Patrícia Helena Maia Alves de Andrade - Controladoria-Geral da União
Analista de Finanças e Controle da CGU, atuando na área de mineração de textos e análise de dados, na Diretoria de Pesquisa e Informações Estratégicas. Atualmente está finalizando o Mestrado Profissional em Computação Aplicada na Universidade de Brasília
Filiação partidária e risco de corrupção de servidores públicos federaisRommel Carvalho
Esta palestra apresenta o trabalho referente a um estudo de caso de aprendizagem de máquina aplicada para mensurar o risco de corrupção de servidores públicos federais usando dados de filiação partidária. Inicialmente, um teste de hipótese verifica a dependência entre corrupção e filiação partidária. Em seguida, são preparados três conjuntos de dados com normalização e três técnicas diferentes de discretização. Usando o ambiente Weka, este trabalho mostra a aplicação de quatro algoritmos de classificação para construir modelos de previsão de risco de corrupção: Redes Bayesianas, Support Vector Machines, Random Forest e Redes Neurais Artificiais com backpropagation.
Para avaliar os modelos, são usadas métricas como precisão, sensibilidade, kappa e acurácia. Por último, o estudo de caso compara o modelo de melhor desempenho construído com um modelo dos especialistas em combate à corrupção. A comparação não apenas confirma afirmações dos especialistas, como também fornece novas visões sobre a relação filiação-corrupção.
Ricardo Silva Carvalho - Controladoria-Geral da União
Graduado em Engenharia da Computação pelo Instituto Tecnológico de Aeronáutica (ITA). Atualmente está finalizando Mestrado em Computação Aplicada na Universidade de Brasília (UnB) trabalhando com projeto na área de Aprendizagem de Máquina. Ocupa cargo de Analista de Finanças e Controle na Controladoria-Geral da União (CGU) com foco na construção de modelos preditivos para mapeamento de risco de corrupção usando mineração de dados. Tem experiência na área de Ciência da Computação, com ênfase em Inteligência Artificial, Aprendizagem de Máquina, Mineração de Dados, Análise de Algoritmos e Engenharia de Software
Uso de mineração de dados e textos para cálculo de preços de referência em co...Rommel Carvalho
Uma das grandes responsabilidades da CGU é identificar as compras do governo com valores diferentes dos praticados pelo mercado. Dessa forma, é possível mensurar o grau de eficiência das compras realizadas pelos órgãos governamentais. Essa informação é útil tanto para o auditor, que é responsável por fiscalizar o uso dos recursos públicos, como para o gestor, que pode melhorar seus processos observando as melhores práticas de outras unidades do governo. Dada a enorme quantidade e a diversidade das compras realizadas pelo Governo, essa análise se torna praticamente inviável sem a ajuda de algum mecanismo automatizado. No entanto, para que essa análise automatizada seja possível, é preciso ter antes de tudo, uma base de dados com os preços médios, ou de referência, para cada produto que se deseja analisar. Apesar de todas as compras do Governo Federal serem inseridas em um sistema único e centralizado, as informações armazenadas não são detalhadas e estruturadas o suficiente para se calcular esses preços de referência.
Essa palestra apresenta a metodologia desenvolvida na CGU, baseada em técnicas de mineração de dados, para extrair as informações necessárias desse sistema centralizado de forma a possibilitar o cálculo de preços de referência para produtos comprados pelo Governo Federal. Além disso, são apresentadas também algumas análises feitas com base no banco de preços criado a partir dessa metodologia de forma a enfatizar sua importância para a melhoria da gestão dos recursos públicos.
Rommel Novaes Carvalho - Controladoria-Geral da União
Coordenador-Geral do Observatório da Despesa Pública da CGU (http://www.cgu.gov.br/assuntos/informacoes-estrategicas/observatorio-da-despesa-publica), realizou seu PhD e Pós-Doc na George Mason University, EUA, na área de Inteligência Artificial, Web Semântica e Mineração de Dados e também é professor do Mestrado Profissional em Computação Aplicada da UnB
Detecção preventiva de fracionamento de comprasRommel Carvalho
Essa palestra apresenta o uso de Mineração de Dados para identificar fracionamentos de forma proativa, ou seja, antes mesmo do fracionamento se concretizar. Dessa forma, é possível alertar o usuário e evitar que a irregularidade aconteça. Nesse trabalho, foram utilizados diversos algoritmos diferentes de classificação, todos baseados em redes bayesianas. Foram analisadas mais de 50 mil compras na área de TI e o modelo final foi capaz de classificar corretamente todos os casos de fracionamento de forma proativa e obteve uma acurácia geral de 99,197%
Rommel Novaes Carvalho - Controladoria-Geral da União
Coordenador-Geral do Observatório da Despesa Pública da CGU (http://www.cgu.gov.br/assuntos/informacoes-estrategicas/observatorio-da-despesa-publica), realizou seu PhD e Pós-Doc na George Mason University, EUA, na área de Inteligência Artificial, Web Semântica e Mineração de Dados e também é professor do Mestrado Profissional em Computação Aplicada da UnB
Identificação automática de tipos de pedidos mais frequentes da LAIRommel Carvalho
Essa palestra apresenta o uso de Mineração de Textos para identificar os principais tipos de pedidos diferentes que são feitos no sistema e-SIC através da LAI. Foram analisados mais de
300 mil pedidos. O processamento desses dados na forma tradicional leva mais de 240 horas, ou 10 dias corridos. Já com o uso de técnicas de Big Data, foi possível diminuir esse processamento para menos de 8 horas
Rommel Novaes Carvalho - Controladoria-Geral da União
Coordenador-Geral do Observatório da Despesa Pública da CGU (http://www.cgu.gov.br/assuntos/informacoes-estrategicas/observatorio-da-despesa-publica), realizou seu PhD e Pós-Doc na George Mason University, EUA, na área de Inteligência Artificial, Web Semântica e Mineração de Dados e também é professor do Mestrado Profissional em Computação Aplicada da UnB
BMAW 2014 - Using Bayesian Networks to Identify and Prevent Split Purchases i...Rommel Carvalho
Presentation given by Rommel N. Carvalho at the 11th Bayesian Modeling Applications Workshop (BMAW 2014) at the 30th Conference on Uncertainty in Artificial Intelligence (UAI 2014) in July 27, 2014, Quebec City, Quebec, Canada. This was a joint work between the Research and Strategic Information Directorate from Brazil's Office of the Comptroller General and the Department of Computer Science from the University of Brasília.
Talk: https://www.youtube.com/watch?v=UVOsztdSQ3A
Paper: http://seor.gmu.edu/~klaskey/BMAW2014/BMAW2014_papers/bmaw2014_paper_6.pdf
Title: Using Bayesian Networks to Identify and Prevent Split Purchases in Brazil.
Abstract: To cope with society's demand for transparency and corruption prevention, the Brazilian Office of the Comptroller General (CGU) has carried out a number of actions, including: awareness campaigns aimed at the private sector; campaigns to educate the public; research initiatives; and regular inspections and audits of municipalities and states. Although CGU has collected information from various different sources - Revenue Agency, Federal Police, and others -, going through all the data in order to find suspicious transactions has proven to be really challenging. In this paper, we present a Data Mining study applied on real data - government purchases - for finding transactions that might become irregular before they are considered as such in order to act proactively. Moreover, we compare the performance of various Bayesian Network (BN) learning algorithms with different parameters in order to fine tune the learned models and improve their performance. The best result was obtained using the Tree Augmented Network (TAN) algorithm and oversampling the minority class in order to balance the data set. Using a 10-fold cross-validation, the model correctly classified all split purchases, it obtained a ROC area of .999, and its accuracy was 99.197%.
Presentation given by Rommel N. Carvalho at the 9th International Workshop on Uncertainty Reasoning for the Semantic Web at the 12th International Semantic Web Conference in October 21, 2013, Sydney, Australia. This was a joint work between the Research and Strategic Information Directorate from Brazil's Office of the Comptroller General and the Department of Computer Science from the University of Brasília.
Title: A GUI for MLN.
Abstract: This paper focuses on the incorporation of the Markov Logic Network (MLN) formalism as a plug-in for UnBBayes, a Java framework for probabilistic reasoning based on graphical models. MLN is a formalism for probabilistic reasoning which combines the capacity of dealing with uncertainty tolerating imperfections and contradictory knowledge based a Markov Network (MN) with the expressiveness of First Order Logic. A MLN provides a compact language for specifying very large MNs and the ability to incorporate, in modular form, large domain of knowledge (expressed in First Order Logic sentences) inside itself. A Graphical User Interface for the software Tuffy was implemented into UnBBayes to facilitate the creation, and inference of MLN models. Tuffy is a Java open source MLN engine.
Presentation given by Rommel N. Carvalho at the 9th International Workshop on Uncertainty Reasoning for the Semantic Web at the 12th International Semantic Web Conference in October 21, 2013, Sydney, Australia. This was a joint work between the Research and Strategic Information Directorate from Brazil's Office of the Comptroller General and the Department of Computer Science from the University of Brasília.
Title: UMP-ST plug-in: a tool for documenting, maintaining, and evolving probabilistic ontologies.
Abstract: Although several languages have been proposed for dealing with uncertainty in the Semantic Web (SW), almost no support has been given to ontological engineers on how to create such probabilistic ontologies (PO). This task of modeling POs has proven to be extremely difficult and hard to replicate. This paper presents the first tool in the world to implement a process which guides users in modeling POs, the Uncertainty Modeling Process for Semantic Technologies (UMP-ST). The tool solves three main problems: the complexity in creating POs; the difficulty in maintaining and evolving existing POs; and the lack of a centralized tool for documenting POs. Besides presenting the tool, which is implemented as a plug-in for UnBBayes, this papers also presents how the UMP-ST plug-in could have been used to build the Probabilistic Ontology for Procurement Fraud Detection and Prevention in Brazil, a proof-of-concept use case created as part of a research project at the Brazilian Office of the Comptroller General (CGU).
Integração do Portal da Copa @ Comissão CMA do Senado FederalRommel Carvalho
Apresentação preparada por Rommel N. Carvalho e apresentada pela Diretora de Sistemas e Informações da Controladoria-Geral da União (CGU), Tatiana Z. Panisset, na reunião da Comissão de Meio Ambiente, Defesa do Consumidor e Fiscalização e Controle (CMA) do Senado Federal (SF). A reunião teve como foco o debate da unificação da entrada de dados dos Portais de Transparência da Copa de 2014 do SF (www.copatransparente.gov.br) e da CGU (http://transparencia.gov.br/copa2014). Mais informações sobre a reunião em http://goo.gl/KCBD6.
As alternativas apresentadas foram discutidas e deliberadas pela CMA com aprovação da colaboração oficial entre o poder Legislativo e o poder Executivo para executar a integração da entrada de dados dos respectivos portais da copa do mundo. Notícias sobre essa colaboração podem ser encontradas em goo.gl/N8cbr, goo.gl/RVMGd, goo.gl/Ze3uJ, goo.gl/6o7BZ e goo.gl/C1CFv.
Título:
O que é e como usar dados abertos governamentais
Resumo:
A Web Semântica visa associar os dados disponibilizados na Web aos seus significados de forma a possibilitar que esses dados sejam compreensíveis tanto por humanos quanto por máquinas. Isso permitirá que tarefas, antes realizadas apenas por humanos, possam agora ser delegadas a máquinas. Técnicas de Web Semântica têm se difundido com o significativo aumento no número de aplicações que fazem uso de ontologias e semântica através de tecnologias como RDF, OWL, dentre outras, e as várias iniciativas espalhadas pelo mundo referente à disponibilização de dados abertos, em especial, de dados abertos governamentais. Dados abertos governamentais são definidos pela W3C – Consórcio da Web, como “a publicação e disseminação na Web de dados gerados pelo Setor Público, compartilhados em formato bruto e aberto, compreensíveis logicamente, de modo a permitir sua reutilização em aplicações digitais desenvolvidas pela sociedade”. O objetivo dessa palestra é apresentar os principais conceitos que norteiam as diversas iniciativas de dados abertos governamentais, a situação atual dessa iniciativa no Brasil, os benefícios que essa iniciativa traz para a sociedade como o uso desses dados abertos para contribuir com a melhoria e transparência da gestão pública.
Palestrante:
Dr. Rommel Novaes Carvalho, Ph.D
Postdoctoral Research Associate – C4I Center @ GMU
Analista de Finanças e Controle – CGU
http://mason.gmu.edu/~rcarvalh
CV resumido:
Rommel Novaes Carvalho é bacharel em Ciência da Computação e Mestre em Informática pela Universidade de Brasília, e doutor em Engenharia de Sistemas e Pesquisa Operacional pela Universidade George Mason, Estados Unidos. Pesquisador em Inteligência Artificial (IA) e membro do Grupo de Pesquisa em Inteligência Artificial da Universidade de Brasília (GIA). Suas áreas de interesse abrangem representação e raciocínio com incerteza na Web Semântica usando inferência bayesiana, mineração de dados, e engenharia de software. Desenvolvedor Java certificado, com experiência em implementação de sistemas de redes probabilísticas, sendo o arquiteto principal do projeto UnBBayes – Framework para raciocino probabilístico, em desenvolvimento pelo GIA desde 2000. Em seu doutorado propôs e implementou a versão 2 para o PR-OWL – Probabilistic OWL, para permitir o reuso de ontologias determinísticas existentes, sua interoperabilidade com ontologias probabilísticas representadas em PR-OWL, e raciocínio misto ontológico e probabilístico. Desde 2005 trabalha na Controladoria-Geral da União como especialista em Tecnologia da Informação. Em 2011, tornou-se pesquisador associado de Pós-Doutorado na George Mason University.
Probabilistic Ontology: Representation and Modeling MethodologyRommel Carvalho
Oral Defense of Doctoral Dissertation
Volgenau School of Engineering, George Mason University
Rommel Novaes Carvalho
Bachelor of Science, University of Brasília, Brazil, 2003
Master of Science, University of Brasília, Brazil, 2008
Probabilistic Ontology: Representation and Modeling Methodology
Tuesday, June 28, 2011, 2:00pm -- 4:00pm
Nguyen Engineering Building, Room 4705
Committee
Kathryn Laskey, Chair
Paulo Costa
Kuo-Chu Chang
David Schum
Larry Kerschberg
Fabio Cozman
Abstract
The past few years have witnessed an increasingly mature body of research on the Semantic Web (SW), with new standards being developed and more complex problems being addressed. As complexity increases in SW applications, so does the need for principled means to cope with uncertainty in SW applications. Several approaches addressing uncertainty representation and reasoning in the SW have emerged. Among these is Probabilistic Web Ontology Language (PR-OWL), which provides Web Ontology Language (OWL) constructs for representing Multi-Entity Bayesian Network (MEBN) theories. However, there are several important ways in which the initial version PR-OWL 1.0 fails to achieve full compatibility with OWL. Furthermore, although there is an emerging literature on ontology engineering, little guidance is available on the construction of probabilistic ontologies.
This research proposes a new syntax and semantics, defined as PR-OWL 2.0, which improves compatibility between PR-OWL and OWL in two important respects. First, PR-OWL 2.0 follows the approach suggested by Poole et al. to formalizing the association between random variables from probabilistic theories with the individuals, classes and properties from ontological languages such as OWL. Second, PR-OWL 2.0 allows values of random variables to range over OWL datatypes.
To address the lack of support for probabilistic ontology engineering, this research describes a new methodology for modeling probabilistic ontologies called Uncertainty Modeling Process for Semantic Technologies (UMP-ST). To better explain the methodology and to verify that it can be applied to different scenarios, this dissertation presents step-by-step constructions of two different probabilistic ontologies. One is used for identifying frauds in public procurements in Brazil and the other is used for identifying terrorist threats in the maritime domain. Both use cases demonstrate the advantages of PR-OWL 2.0 over its predecessor.
SWRL-F - A Fuzzy Logic Extension of the Semantic Web Rule LanguageRommel Carvalho
Presentation given by Tomasz Wlodarczyk at the 6th Uncertainty Reasoning for the Semantic Web Workshop at the 9th International Semantic Web Conference in 2010.
Paper: SWRL-F - A Fuzzy Logic Extension of the Semantic Web Rule Language
Abstract: Enhancing Semantic Web technologies with an ability to express uncertainty and imprecision is widely discussed topic. While SWRL can provide additional expressivity to OWL-based ontologies, it does not provide any way to handle uncertainty or imprecision. We introduce an extension of SWRL called SWRL-F that is based on SWRL rule language and uses SWRL's strong semantic foundation as its formal underpinning. We extend it with a SWRL-F ontology to enable fuzzy reasoning in the rule base. The resulting language provides small but powerful set of fuzzy operations that do not introduce inconsistencies in the host ontology.
Default Logics for Plausible Reasoning with Controversial AxiomsRommel Carvalho
Presentation given by Thomas Scharrenbach at the 6th Uncertainty Reasoning for the Semantic Web Workshop at the 9th International Semantic Web Conference in 2010.
Paper: Default Logics for Plausible Reasoning with Controversial Axioms
Abstract: Using a variant of Lehmann's Default Logics and Probabilistic Description Logics we recently presented a framework that invalidates those unwanted inferences that cause concept unsatisfiability without the need to remove explicitly stated axioms. The solutions of this methods were shown to outperform classical ontology repair w.r.t. the number of inferences invalidated. However, conflicts may still exist in the knowledge base and can make reasoning ambiguous. Furthermore, solutions with a minimal number of inferences invalidated do not necessarily minimize the number of conflicts. In this paper we provide an overview over finding solutions that have a minimal number of conflicts while invalidating as few inferences as possible. Specifically, we propose to evaluate solutions w.r.t. the quantity of information they convey by recurring to the notion of entropy and discuss a possible approach towards computing the entropy w.r.t. an ABox.
A workshop hosted by the South African Journal of Science aimed at postgraduate students and early career researchers with little or no experience in writing and publishing journal articles.
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AFCEA 2010 - High Level Fusion and Predictive Situational Awareness with Probabilistic Ontologies
1. High Level Fusion and
Predictive Situational
Awareness with
Probabilistic Ontologies
Paulo Costa, KC Chang, Kathryn Laskey, & Rommel Carvalho
Center of Excellence in C4I
George Mason University
1
2. Uncertainty and Timelessness
“…The commander is compelled during the whole
campaign to reach decisions on the basis of situations that
cannot be predicted … The problem is to grasp, in
innumerable special cases, the actual situation which is
covered by the mist of uncertainty, to appraise the facts
correctly and to guess the unknown elements, to reach a
decision quickly and then to carry it out forcefully and
relentlessly.”
Helmuth von Moltke, 1800-1891
Paret, P.; Craig; A.G.; Gilbert, F. (1986) Makers of Modern Strategy: From Machiavelli to
the Nuclear Age. London, UK: Oxford University Press (Page 289)
Costa, Chang, Laskey, Carvalho 2 GMU - AFCEA Symposium - May 18, 2010
3. Agenda
•!Knowledge Exchange in C 2
•!Ontologies
•!Probabilistic Ontologies
•!Case Study: PROGNOS
Costa, Chang, Laskey, Carvalho 3 GMU - AFCEA Symposium - May 18, 2010
4. What is Preventing True Netcentricity?
•! Inability to produce a dynamic, comprehensive, and
accurate battlespace picture for the warfighter that
integrates tactical data from multiple intelligence
sources.
•! Lack of automated techniques to integrate data
(geolocation, detection, and identification) from multiple
intelligence sources, in a consistent and timely manner.
•! Lack of accurate and timely information about
battlespace objects and events to support warfighter
decision making in an asymmetric warfare.
Costa, Chang, Laskey, Carvalho 4 GMU - AFCEA Symposium - May 18, 2010
5. Knowledge and Data Fusion
Uncertainty
Data Fusion Association Estimation
Product
Level Process Process
L3 Evaluation Game- Estimated
Impact (situation to Theoretic Situation
Assessment actor’s goals) Interaction Utility
L2 Relationship Estimated
Situation (entity-to- Relation Situation
Assessment entity) State
L1 Assignment
Attributive Estimated
Object (observation-
State Entity State
Assessment to-entity)
L0 Assignment
Estimated
Signal (observation- Detection
Signal State
Assessment to-feature)
Cognitive Hierarchy JDL Data fusion levels
FM 6-0: Mission Command: Command and Control of White, F.E., “A Model for Data Fusion”, Proc. 1st National
Army Forces. Aug 2003. Symposium on Sensor Fusion, 1988
Costa, Chang, Laskey, Carvalho 5 GMU - AFCEA Symposium - May 18, 2010
6. Shortfalls of Current Approaches
•! Either cannot achieve fusion levels 2 and above
(JDL model), or can do so only in controlled
environments (limited scalability and expressivity).
•! Limited ability to cope with uncertainty, typically
ignoring or mishandling it.
•! Can handle only standardized messages, special
-case scenarios, and specific sensor types, leading
to interoperability issues and less than optimal use
of available information.
Costa, Chang, Laskey, Carvalho 6 GMU - AFCEA Symposium - May 18, 2010
7. The Missing Pieces
Connect reports to
situations
!"#$"%"&'()&*( 8-7.(9"6"4((
$")%+&(( :)')((
,-'.( ;/%-+&(
/&0"$')-&'1(
5*6)&0"*(
)47+$-'.3%(
)&*(
(3"'.+*%(
Operate in the
2"3)&'-0)441(
“fog of war” (((((),)$"(
%1%'"3%(
Cope with complexity
Link information to knowledge
Costa, Chang, Laskey, Carvalho 7 GMU - AFCEA Symposium - May 18, 2010
8. The Way Forward
•! Rigorous mathematical foundation and efficient algorithms to
combine data from diverse sources for reliable predictive
situation assessment
•! Automated techniques to reduce warfighter's information
processing load and provide timely actionable knowledge to
decision makers
•! Interoperable methodologies for propagating uncertainty
through the integration process to characterize and
distinguish situational conditions for predictive analysis and
impact assessment under various behaviors and
environments
•! Semantically aware systems for interoperability in net-centric
environment
Costa, Chang, Laskey, Carvalho 8 GMU - AFCEA Symposium - May 18, 2010
9. C4I Center’s Multi-Disciplinary Approach
•! Developing interoperable
enabling technologies based
on Multi-entity Bayesian
Networks, Probabilistic
Ontologies, and pragmatic
frames to support Net
Centric operations
•! Developing mathematically rigorous and computationally
efficient algorithms based on Spatio-Temporal Hypothesis
Management and Efficient Hybrid Inference to provide
dependable predictive situational awareness Developing formal
approaches and tools to represent command intent and to
reduce ambiguity in operational communications.
Costa, Chang, Laskey, Carvalho 9 GMU - AFCEA Symposium - May 18, 2010
10. Interoperation vs. Integration
Interoperation of systems Integration of systems
•! participants remain autonomous and •! participants are assimilated into whole, losing
•!participants are assimilated into whole,
independent losing autonomyindependence
autonomy and and independence
•! loosely coupled •!ightly coupled
•!t
tightly coupled
•! interaction rules are soft coded and •!nteraction rules are hard coded and coco-
interaction rules
•!i -dependent are hard coded and
encapsulated
•! local data vocabularies and ontologies for •! global data
dependent vocabulary and ontology for
interpretation persist •!global data vocabulary and ontology for
interpretation adopted
•! share information via mediation •! share information conforming to strict standards
interpretation adopted
•! asynchronous data transfer •! synchronous data transfer
•!share information conforming to strict stand
reusability
composability Vs. fit-to-purpose
responsiveness
flexibility
NOT Polar Opposites!
SPECTRUM of INTERACTION MODES
* adapted from: J.T. Pollock, R. Hodgson, “Adaptive Information”, Wiley-Interscience, 2004
Costa, Chang, Laskey, Carvalho 10 GMU - AFCEA Symposium - May 18, 2010
11. Example: Kill chain
find fix track target engage assess
interoperation integration
Field of view, scope
Information-centric
!"#$%&"'%()*"+
•! The kill chain illustrates the co-existence of interoperation and integration
modes of component interaction.
•! Early activities in the chain are characterized by larger field of view and
have more information-centric functions than do later activities. They need
the loose coupling and flexibility of interoperation.
•! Later activities are more action-centric requiring the tight coupling and
responsiveness of integrated components.
Costa, Chang, Laskey, Carvalho 11 GMU - AFCEA Symposium - May 18, 2010
12. Linguistic Levels of Information
Exchange and Interoperability
System Participant System Participant
Linguistic Level of ! A System of Systems interoperates at this level if :
Information Exchange
Pragmatic – how information in messages is The receiver re-acts to the message in a manner that the
used sender intends (assuming non-hostility in the collaboration).
Semantic – shared understanding of meaning of The receiver assigns the same meaning as the sender did to
messages the message.
Syntactic –common rules governing The consumer is able to receive and parse the sender’s
composition and transmitting of messages message
Costa, Chang, Laskey, Carvalho GMU - AFCEA Symposium - May 18, 2010
13. Agenda
•!Knowledge Exchange in C 2
•!Ontologies
•!Probabilistic Ontologies
•!Case Study: PROGNOS
Costa, Chang, Laskey, Carvalho 13 GMU - AFCEA Symposium - May 18, 2010
14. Ontologies
•! In Philosophy: the study of nature of being and knowing
•! In Information Systems: many definitions
an ontology is a set of concepts - such as
An Explicit formal specification on how to An Ontology formally defines a common
things, events, and relations - that are specified
represent the objects, concepts, and other set of terms that are used to describe and
in some way (such as specific natural
entities that are assumed to exist in some represent a domain. Ontologies can be
language) in order to create an agreed-upon
area of interest an the relationships among used by automated tools to power
vocabulary for exchanging information.
them. (dictionary.com) advanced services such as more accurate
(whatis.com)
Web search, intelligent software agents
and knowledge management. (Owl Use
In information science, an ontology is the Is a formal specification of a Cases)
product of an attempt to formulate an conceptualization (Gruber)
exhaustive and rigorous conceptual schema
about a domain. An ontology is typically a An ontology models the vocabulary and A partial specification of a conceptual
hierarchical data structure containing all the meaning of domains of interest: the objects vocabulary to be used for formulating
relevant entities and their relationships and (things) in domains; the relationships among knowledge-level theories about a domain of
rules within that domain (Wikipedia.org). those things; the properties, functions, and discourse. The fundamental role of an
processes involving those things; and ontology is to support knowledge sharing and
constraints on and rules about those things reuse. (The Internet Reasoning Services
(DaConta et al., 2003) project - IRS)
What is really important?
Costa, Chang, Laskey, Carvalho 14 GMU - AFCEA Symposium - May 18, 2010
15. Semantics in Data Fusion
•! Information in the battlefield comes from reports
from diverse sources, in distinct syntax, and with
different meanings.
•! Effective interoperability requires understanding the
relationship between reports from different systems
and the events reported upon
•! Semantically aware systems are essential to
distributed knowledge fusion.
•! Ontologies are a means to semantic awareness
Costa, Chang, Laskey, Carvalho 15 GMU - AFCEA Symposium - May 18, 2010
17. Ontologies vs. OO
Ontologies Databases / OO
•! Rely on logical reasoners to •! Rigidly defined classes that
infer class relationships and govern the system behavior
instance membership
•! All instances are created as
•! Flexible format that adapts members of some class.
its class structure as new
information is learned
•! Changing a class affects all of
its instances
•! Open World Assumption / •! Closed World Assumption /
Well suited for open Well suited for top down
systems governance
Costa, Chang, Laskey, Carvalho 17 GMU - AFCEA Symposium - May 18, 2010
18. Ontologies and Uncertainty
•! There are many kinds of uncertainty, e.g.:
!! Noise in sensors
!! Incorrect, incomplete, deceptive human intelligence
!! Lack of understanding of cause and effect mechanisms in the world
•! Representing and reasoning with uncertainty is essential
•! But...
Costa, Chang, Laskey, Carvalho 18 GMU - AFCEA Symposium - May 18, 2010
20. Deterministic Reasoning
(... is not always suitable to the problem)
•! All Birds lay eggs
•! Many aquatic birds have Duck-like bills
•! Many aquatic birds have webbed feet (like ducks)
•! All aquatic birds swim very well and can hold breath for a
long period
•! Joe:
!! Is an egg-laying animal
!! Has a Duck-like bill
!! Has webbed feet
!! Swin very well and can hold breath for a long period
•! Therefore: Joe is a…
Costa, Chang, Laskey, Carvalho 20 GMU - AFCEA Symposium - May 18, 2010
21. Joe is a Duck-Billed Platypus
(a mammal)
•! It lays eggs like a bird or a reptile
(this makes it a monotreme
mammal)
•! The males have poison like a snake
in spurs on their hind legs. The
poison can kill a dog and cause
extreme pain in people.
•! They have a bill like a duck.
•! They have a tail like a beaver.
•! They have webbed feet like a duck.
•! The mother's milk comes out through
glands on her skin and the babies
lick it off of her fur.
Costa, Chang, Laskey, Carvalho 21 GMU - AFCEA Symposium - May 18, 2010
22. Agenda
•!Knowledge Exchange in C 2
•!Ontologies
•!Probabilistic Ontologies
•!Case Study: PROGNOS
Costa, Chang, Laskey, Carvalho 22 GMU - AFCEA Symposium - May 18, 2010
23. A Pragmatical View
Evidence
Knowledge Base New Data
Racer
Knowledge Base
Logic Reasoner
UnBBayes
Uncertainty-free Information
MEBN
Logical Reasoning
Evidence Reasoners
Probabilistic KB
Bayesian Reasoner
Evidence
Enhanced Knowledge
Bayesian Reasoning
Costa, Chang, Laskey, Carvalho GMU - AFCEA Symposium - May 18, 2010
24. How about Bayesian Networks?
Costa, Chang, Laskey, Carvalho GMU - AFCEA Symposium - May 18, 2010
25. Why not BNs?
Costa, Chang, Laskey, Carvalho GMU - AFCEA Symposium - May 18, 2010
27. MEBN Fragments
•! Building blocks that collectively
form a model (MTheory)
•! Each one stores a specific
"Chunk of knowledge"
Costa, Chang, Laskey, Carvalho 27 GMU - AFCEA Symposium - May 18, 2010
28. PR-OWL Probabilistic Ontology Language
•! Upper ontology written in W3C-recommended OWL ontology
language.
•! Represents probabilistic knowledge in XML-compliant format.
•! Based on MEBN, a probabilistic logic with first-order
expressive power
•! Open-source, freely available solution for representing
knowledge and associated uncertainty.
•! Reasoner under development
in collaboration with University
of Brasilia
Costa, Chang, Laskey, Carvalho 28 GMU - AFCEA Symposium - May 18, 2010
35. High-Level Design Concept
o! Integrate the enabling technologies in a distributed system architecture
•! Represent domain knowledge as MEBN fragments that define situation variables
•! MFrags are small and model “small pieces” of knowledge for building complex model
o! Perform hypothesis management for predictive situation and impact assessment
•! Match new evidence to existing hypotheses and/or nominate new hypotheses via MC2HM,
generating an approximation to the posterior distribution of hypotheses given evidence
•! Pass results to the inference module, which builds a Bayesian network to predict future events
o! Enable Distributed net-centric SOA
•! Probabilistic ontologies fill a key gap in semantic matching technology, facilitate wide-spread usage
of Web Services for efficient resource sharing in distributed FORCENet. environments
Costa, Chang, Laskey, Carvalho GMU - AFCEA Symposium - May 18, 2010
36. Architecture Components
•! Interoperability with
FORCENet and external
systems via a set of
interchange POs
•! Hybrid reasoning in
support for a Hypothesis
Management engine
•! Internal entity storage
module in FORCENet
formatting
•! Task-specific POs for
optimal mission-based
inferences, ensuring
modularity and helping
scalability
•! Domain-agnostic Prognos Core library •! Simulation module for both
in support to general reasoning and system training and evaluation
Hypothesis Management
Costa, Chang, Laskey, Carvalho 36 GMU - AFCEA Symposium - May 18, 2010