Innovative Platform for Designing Hybrid Collaborative & Context-Aware Data Mining Scenarios

The process of knowledge discovery involves nowadays a major number of techniques. Context-Aware Data Mining (CADM) and Collaborative Data Mining (CDM) are some of the recent ones. the current research proposes a new hybrid and efficient tool to design prediction models called Scenarios Platform-Collaborative & Context-Aware Data Mining (SP-CCADM). Both CADM and CDM approaches are included in the new platform in a flexible manner; SP-CCADM allows the setting and testing of multiple configurable scenarios related to data mining at once. The introduced platform was successfully tested and validated on real life scenarios, providing better results than each standalone technique-CADM and CDM. Nevertheless, SP-CCADM was validated with various machine learning algorithms-k-Nearest Neighbour (k-NN), Deep Learning (DL), Gradient Boosted Trees (GBT) and Decision Trees (DT). SP-CCADM makes a step forward when confronting complex data, properly approaching data contexts and collaboration between data. Numerical experiments and statistics illustrate in detail the potential of the proposed platform.Comment: 15 figure

A Context-Aware mHealth System for Online Physiological Monitoring in Remote Healthcare

Physiological or biological stress is an organism’s response to a stressor such as an environmental condition or a stimulus. The identification of physiological stress while performing the activities of daily living is an important field of health research in preventive medicine. Activities initiate a dynamic physiological response that can be used as an indicator of the overall health status. This is especially relevant to high risk groups; the assessment of the physical state of patients with cardiovascular diseases in daily activities is still very difficult. This paper presents a context-aware telemonitoring platform, IPM-mHealth, that receives vital parameters from multiple sensors for online, real-time analysis. IPM-mHealth provides the technical basis for effectively evaluating patients’ physiological conditions, whether inpatient or at home, through the relevance between physical function and daily activities. The two core modules in the platform include: 1) online activity recognition algorithms based on 3-axis acceleration sensors and 2) a knowledge-based, conditional-reasoning decision module which uses context information to improve the accuracy of determining the occurrence of a potentially dangerous abnormal heart rate. Finally, we present relevant experiments to collect cardiac information and upper-body acceleration data from the human subjects. The test results show that this platform has enormous potential for use in long-term health observation, and can help us define an optimal patient activity profile through the automatic activity analysis

A reusable application framework for context-aware mobile patient monitoring systems

The development of Context-aware Mobile Patient Monitoring Systems (CaMPaMS) using wireless sensors is very complex. To overcome this problem, the Context-aware Mobile Patient Monitoring Framework (CaMPaMF) was introduced as an ideal reuse technique to enhance the overall development quality and overcome the development complexity of CaMPaMS. While a few studies have designed reusable CaMPaMFs, there has not been enough study looking at how to design and evaluate application frameworks based on multiple reusability aspects and multiple reusability evaluation approaches. Furthermore, there also has not been enough study that integrates the identified domain requirements of CaMPaMS. Therefore, the aim of this research is to design a reusable CaMPaMF for CaMPaMS. To achieve this aim, twelve methods were used: literature search, content analysis, concept matrix, feature modelling, use case assortment, domain expert review, model-driven architecture approach, static code analysis, reusability model approach, prototyping, amount of reuse calculation, and software expert review. The primary outcome of this research is a reusable CaMPaMF designed and evaluated to capture reusability from different aspects. CaMPaMF includes a domain model validated by consultant physicians as domain experts, an architectural model, a platform-independent model, a platform-specific model validated by software expert review, and three CaMPaMS prototypes for monitoring patients with hypertension, epilepsy, or diabetes, and multiple reusability evaluation approaches. This research contributes to the body of software engineering knowledge, particularly in the area of design and evaluation of reusable application frameworks. Researchers can use the domain model to enhance the understanding of CaMPaMS domain requirements, thus extend it with new requirements. Developers can also reuse and extend CaMPaMF to develop various CaMPaMS for different diseases. Software industries can also reuse CaMPaMF to reduce the need to consult domain experts and the time required to build CaMPaMS from scratch, thus reducing the development cost and time

CAS-MINE: Providing personalized services in context-aware applications by means of generalized rules

Context-aware systems acquire and exploit information on the user context to tailor services to a particular user, place, time, and/or event. Hence, they allowservice providers to adapt their services to actual user needs, by offering personalized services depending on the current user context. Service providers are usually interested in profiling users both to increase client satisfaction and to broaden the set of offered services. Novel and efficient techniques are needed to tailor service supply to the user (or the user category) and to the situation inwhich he/she is involved. This paper presents the CAS-Mine framework to efficiently discover relevant relationships between user context data and currently asked services for both user and service profiling. CAS-Mine efficiently extracts generalized association rules, which provide a high-level abstraction of both user habits and service characteristics depending on the context. A lazy (analyst-provided) taxonomy evaluation performed on different attributes (e.g., a geographic hierarchy on spatial coordinates, a classification of provided services) drives the rule generalization process. Extracted rules are classified into groups according to their semantic meaning and ranked by means of quality indices, thus allowing a domain expert to focus on the most relevant patterns. Experiments performed on three context-aware datasets, obtained by logging user requests and context information for three real applications, show the effectiveness and the efficiency of the CAS-Mine framework in mining different valuable types of correlations between user habits, context information, and provided services

Hacia un modelo integrado de procesamiento de flujos de datos

El presente paper presenta un modelo integrado de procesamiento de flujos de datos con el fin de mejorar la toma de decisiones basada en contextos mediante la incorporación de metadatos basados en una ontología de medición. En particular se discute la recolección-adaptación de datos dentro del modelo integrado de procesamiento, y se aborda la problemática de la definición de un esquema para el intercambio continuo de mediciones basadas en un marco conceptual de medición y evaluación, como así también el protocolo asociado a la transmisión de las mismas. Dicho esquema y protocolo, permiten el intercambio de metadatos vinculados a mediciones y sus contextos asociados, con el objeto de permitir un análisis consistente de los mismos que contribuya a una mejora en la toma de decisión susceptible al contexto.Workshop de Ingeniería de Software y Bases de Datos (WISBD)Red de Universidades con Carreras en Informática (RedUNCI

Hacia un modelo integrado de procesamiento de flujos de datos

El presente paper presenta un modelo integrado de procesamiento de flujos de datos con el fin de mejorar la toma de decisiones basada en contextos mediante la incorporación de metadatos basados en una ontología de medición. En particular se discute la recolección-adaptación de datos dentro del modelo integrado de procesamiento, y se aborda la problemática de la definición de un esquema para el intercambio continuo de mediciones basadas en un marco conceptual de medición y evaluación, como así también el protocolo asociado a la transmisión de las mismas. Dicho esquema y protocolo, permiten el intercambio de metadatos vinculados a mediciones y sus contextos asociados, con el objeto de permitir un análisis consistente de los mismos que contribuya a una mejora en la toma de decisión susceptible al contexto.Workshop de Ingeniería de Software y Bases de Datos (WISBD)Red de Universidades con Carreras en Informática (RedUNCI

Data mining by means of generalized patterns

The thesis is mainly focused on the study and the application of pattern discovery algorithms that aggregate database knowledge to discover and exploit valuable correlations, hidden in the analyzed data, at different abstraction levels. The aim of the research effort described in this work is two-fold: the discovery of associations, in the form of generalized patterns, from large data collections and the inference of semantic models, i.e., taxonomies and ontologies, suitable for driving the mining proces

Método de modelagem do contexto estratégico para sistemas baseados em conhecimento

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Engenharia e Gestão do Conhecimento, Florianópolis, 2013.A Engenharia do Conhecimento dedica-se à modelagem de conhecimento e ao desenvolvimento de sistemas de conhecimento. Um de seus principais desafios está na compreensão do contexto de aplicação de seus métodos e técnicas e na conexão entre esses e o plano estratégico da organização beneficiada pelo projeto. Nesta dissertação, realizou-se pesquisa aplicada para estabelecer um método de modelagem do contexto estratégico para sistemas baseados em conhecimento (SBC). O método agrupa ferramentais, metodologias e técnicas de engenharia do conhecimento e ontologias, com o objetivo de contextualizar o conhecimento que forma a base de um SBC no plano estratégico de sua aplicação. O método tem fundamentos na visão sistêmica de Bunge (1997; 2000; 2004), ampliada pela abordagem de engenharia do conhecimento das metodologias CommonKADS e KAMET II (para identificação do contexto em que o conhecimento está inserido). A engenharia de ontologias é aplicada na representação formal do conhecimento, com o emprego de diretrizes e técnicas da metodologia NeOn e do método OntoKEM. O método foi aplicado em processo de explicitação do conhecimento contextual, em um projeto de pesquisa desenvolvimento e inovação. Os resultados da pesquisa corroboram com estudos que evidenciam os benefícios do conhecimento contextualizado para a compreensão do problema estratégico que envolve um SBC. Além disso, verificou-se que a identificação e modelagem do contexto estratégico pode servir, também, como fonte comum de conhecimento para as atividades técnicas de concepção de um SBC, tais como análises de viabilidade do sistema, extração de requisitos funcionais e requisitos não funcionais, elaboração de casos de uso e implantação de processos e cultura para viabilizar o desenvolvimento e uso de tais sistemas. Abstract : Knowledge Engineering is dedicated to the modeling of knowledge and the development of knowledge systems. One of the main challenges is to understand the context of applying methods and techniques, the connection between these and the strategic plan of the organization, in order to understand the potential benefits from the project. In this dissertation, we researched how to establish a method of modeling the strategic context for knowledge-based systems (KBS). The method combines tools, methodologies and techniques of knowledge engineering and ontologies in order to contextualize the knowledge that forms the basis of a strategic plan for applying the methods and techniques of KBS. The method has foundations in the systemic vision of Bunge (1997, 2000, 2004), supported by the approach of methodologies from knowledge engineering, like the CommonKADS and KAMET II methodologies (to identify the context of the knowledge being analysed). The ontology engineering is applied to the formal representation of knowledge, with the use of guidelines and techniques from the NEON methodology and from the OntoKEM method. The method was applied in the case study, in order to explain the contextual knowledge, in a research project of development and innovation. The survey results corroborate studies that show the benefits of contextual knowledge for understanding the strategic problem that involves a KBS. It was found that the identification and modeling of strategic context may also serve as a source of common knowledge to design the technical activities of an KBS, such as, analysis of feasibility from system development, extraction of functional and non-functional requirements. Furthermore can be serve for the elaboration of use cases, and implementation of processes and culture to enable the development and use of such systems