We propose a data mining approach to predict human wine taste preferences that is based on easily... more We propose a data mining approach to predict human wine taste preferences that is based on easily available analytical tests at the certification step. A large dataset (when compared to other studies in this domain) is considered, with white and red vinho verde samples (from Portugal). Three regression techniques were applied, under a computationally efficient procedure that performs simultaneous variable and model selection.
In this work, the main goal is to develop and evaluate a number of optimization algorithms in the... more In this work, the main goal is to develop and evaluate a number of optimization algorithms in the task of improving Quality of Service levels in TCP/IP based networks, by configuring the routing weights of link-state protocols such as OSPF. Since this is a complex problem, some meta-heuristics from the Evolutionary Computation arena were considered, working over a mathematical model that allows for flexible cost functions, taking into account several measures of the network behavior such as network congestion and end-to-end delays.
Abstract The forecast of Internet traffic is an important issue that has received few attention f... more Abstract The forecast of Internet traffic is an important issue that has received few attention from the computer networks field. By improving this task, efficient traffic engineering and anomaly detection tools can be created, resulting in economic gains from better resource management. This paper presents a neural network ensemble (NNE) for the prediction of TCP/IP traffic using a time series forecasting (TSF) point of view. Several experiments were devised by considering real-world data from two large Internet Service Providers.
A avaliação da qualidade é um factor chave para a indústria da carne, onde o objectivo primordial... more A avaliação da qualidade é um factor chave para a indústria da carne, onde o objectivo primordial reside na satisfação das necessidades dos consumidores. Em particular, a tenrura é considerada a mais importante característica que afecta o paladar da carne. Neste trabalho, é proposto um Conjunto de Redes Neuronais1, baseado na selecção de atributos via um procedimento de Análise de Sensibilidade, para a predição da tenrura da carne de cordeiros.
To increase effectiveness in their marketing and CRM activities many organizations are adopting s... more To increase effectiveness in their marketing and CRM activities many organizations are adopting strategies of Database Marketing (DBM). DBM faces today new challenges in business knowledge. Currently DBM strategies are mainly approached by classical statistical inference, which may fail when complex, multi-dimensional, and incomplete data is available. An alternative is to use Knowledge Discovery from Databases (KDD), which aims at automatic pattern extraction using Data Mining (DM) techniques.
Alternative approaches for Time Series Forecasting (TSF) emerged from the Artificial Intelligence... more Alternative approaches for Time Series Forecasting (TSF) emerged from the Artificial Intelligence arena, where optimization algorithms inspired on natural selection processes, such as Genetic Algorithms (GAs) are popular. The present work reports on a two-level architecture, where a (meta-level) binary GA will search for the best TSF model, being the parameters optimized by a (low-level) GA, which encodes real values.
Abstract Jet Grouting (JG) is a Geotechnical Engineering technique that is characterized by a gre... more Abstract Jet Grouting (JG) is a Geotechnical Engineering technique that is characterized by a great versatility, being the best solution for several soil treatment improvement problems. However, JG lacks design rules and quality control. As the result, the main JG works are planned from empirical rules that are often too conservative.
A number of Traffic Engineering (TE) approaches have been recently proposed to improve the perfor... more A number of Traffic Engineering (TE) approaches have been recently proposed to improve the performance of network routing protocols, both developed over MPLS and intra-domain protocols such as OSPF. In this work, a TE approach is proposed for routing optimization in scenarios where unicast and multicast demands are simultaneously present. Evolutionary Algorithms are used as the optimization engine with overall network congestion as the objective function.
Scholarly communication describes the process of sharing and publishing of research findings. Thi... more Scholarly communication describes the process of sharing and publishing of research findings. This report provides some useful guidelines for improving a key scholarly communication aspect: the writing of scientific documents (eg journal articles, conference papers, Doctor of Philosophy thesis).
Abstract This paper quantifies the impact of topological characteristics on the performance of si... more Abstract This paper quantifies the impact of topological characteristics on the performance of single radio multichannel IEEE 802.11 mesh networks. Topological characteristics are the number of nodes per subnetwork, the hop count, the neighbor node density, the hidden nodes, the number of nodes in the neighborhood of the gateway, and the hidden nodes in the neighborhood of the gateway. Network performance metrics are throughput, fairness and delay.
Sometimes, the soil foundation is inadequate for constructions purpose (soft-soils). In these cas... more Sometimes, the soil foundation is inadequate for constructions purpose (soft-soils). In these cases there is need to improve its mechanical and physical properties. For this purpose, there are several geotechnical techniques where Jet Grouting (JG) is highlighted. In many geotechnical structures, advance design incorporates the ultimate limit state (ULS) and the serviceability limit state (SLS) design criteria, for which uniaxial compressive strength and deformability properties of the improved soils are needed.
Strength and stiffness are the mechanical properties currently used in geotechnical works design,... more Strength and stiffness are the mechanical properties currently used in geotechnical works design, namely in jet grouting (JG) treatments. However, when working with this soil improvement technology, due to its inherent geological complexity and high number of variables involved, such design is a hard, perhaps very hard task.
O serviço de correio electrónico assume uma crescente importância na sociedade actual e, em parti... more O serviço de correio electrónico assume uma crescente importância na sociedade actual e, em particular, no âmbito dos serviços de comunicação que hoje em dia são alvo preferencial de utilização por parte dos utilizadores da Internet. No entanto, são ainda muitos os desafios que se colocam a este serviço, nomeadamente no que diz respeito à crescente proliferação do fenómeno de correio electrónico não solicitado.
To increase effectiveness in their marketing and Customer Relationship Manager activities, many o... more To increase effectiveness in their marketing and Customer Relationship Manager activities, many organizations are adopting strategies of Database Marketing (DBM). Nowadays, DBM faces new challenges in business knowledge since current strategies are mainly approached by classical statistical inference, which may fail when complex, multi-dimensional and incomplete data is available.
Forecasting Internet traffic is receiving an increasing attention from the computer networks doma... more Forecasting Internet traffic is receiving an increasing attention from the computer networks domain. Indeed, by improving this task efficient traffic engineering and anomaly detection tools can be developed, leading to economic gains due to better resource management. This paper presents a Neural Network (NN) approach to predict TCP/IP traffic for all links of a backbone network, using both univariate and multivariate strategies.
Certification and quality assessment are crucial issues within the wine industry. Currently, wine... more Certification and quality assessment are crucial issues within the wine industry. Currently, wine quality is mostly assessed by physicochemical (eg alcohol levels) and sensory (eg human expert evaluation) tests. In this paper, we propose a data mining approach to predict wine preferences that is based on easily available analytical tests at the certification step. A large dataset is considered with white vinho verde samples from the Minho region of Portugal.
Classical Machine Learning methods are usually developed to work in static data sets. Yet, real w... more Classical Machine Learning methods are usually developed to work in static data sets. Yet, real world data typically changes over time and there is the need to develop novel adaptive learning algorithms. In this work, a number of algorithms, combining Neural Network learning models and Evolutionary Computation optimization techniques, are compared, being held several simulations based on artificial and real world problems.
This paper addresses the problem of automatic detection and prediction of abnormal human behaviou... more This paper addresses the problem of automatic detection and prediction of abnormal human behaviours in public spaces. For this propose a novel classifier, called N-ary trees, is presented. The classifier processes time series of attributes like the object position, velocity, perimeter and area, to infer the type of action performed. This innovative classifier can detect three types of events: normal; unusual; or abnormal events.
This article presents three methods to forecast accurately the amount of traffic in TCP= IP based... more This article presents three methods to forecast accurately the amount of traffic in TCP= IP based networks: a novel neural network ensemble approach and two important adapted time series methods (ARIMA and Holt-Winters). In order to assess their accuracy, several experiments were held using real-world data from two large Internet service providers. In addition, different time scales (5min, 1h and 1 day) and distinct forecasting lookaheads were analysed.
This paper introduces the INTCare system, an intelligent decision support system for intensive me... more This paper introduces the INTCare system, an intelligent decision support system for intensive medicine. The system aims at the automation of the Knowledge Discovery Process by using autonomous agents that are responsible for the various constituent steps. The system enables automation of data acquisition and model updating avoiding human intervention. We present the first impressions after the deployment of INTCare in a real environment (Intensive Care Unit of the Hospital de Santo António, Oporto, Portugal) where it is supporting the physicians' decisions by means of prognostic Data Mining models. In particular, these techniques are used to predict organ failure and mortality assessment. The main intention is to change the current reactive behaviour to a pro-active one, enhancing the Quality of Service.
We propose a data mining approach to predict human wine taste preferences that is based on easily... more We propose a data mining approach to predict human wine taste preferences that is based on easily available analytical tests at the certification step. A large dataset (when compared to other studies in this domain) is considered, with white and red vinho verde samples (from Portugal). Three regression techniques were applied, under a computationally efficient procedure that performs simultaneous variable and model selection.
In this work, the main goal is to develop and evaluate a number of optimization algorithms in the... more In this work, the main goal is to develop and evaluate a number of optimization algorithms in the task of improving Quality of Service levels in TCP/IP based networks, by configuring the routing weights of link-state protocols such as OSPF. Since this is a complex problem, some meta-heuristics from the Evolutionary Computation arena were considered, working over a mathematical model that allows for flexible cost functions, taking into account several measures of the network behavior such as network congestion and end-to-end delays.
Abstract The forecast of Internet traffic is an important issue that has received few attention f... more Abstract The forecast of Internet traffic is an important issue that has received few attention from the computer networks field. By improving this task, efficient traffic engineering and anomaly detection tools can be created, resulting in economic gains from better resource management. This paper presents a neural network ensemble (NNE) for the prediction of TCP/IP traffic using a time series forecasting (TSF) point of view. Several experiments were devised by considering real-world data from two large Internet Service Providers.
A avaliação da qualidade é um factor chave para a indústria da carne, onde o objectivo primordial... more A avaliação da qualidade é um factor chave para a indústria da carne, onde o objectivo primordial reside na satisfação das necessidades dos consumidores. Em particular, a tenrura é considerada a mais importante característica que afecta o paladar da carne. Neste trabalho, é proposto um Conjunto de Redes Neuronais1, baseado na selecção de atributos via um procedimento de Análise de Sensibilidade, para a predição da tenrura da carne de cordeiros.
To increase effectiveness in their marketing and CRM activities many organizations are adopting s... more To increase effectiveness in their marketing and CRM activities many organizations are adopting strategies of Database Marketing (DBM). DBM faces today new challenges in business knowledge. Currently DBM strategies are mainly approached by classical statistical inference, which may fail when complex, multi-dimensional, and incomplete data is available. An alternative is to use Knowledge Discovery from Databases (KDD), which aims at automatic pattern extraction using Data Mining (DM) techniques.
Alternative approaches for Time Series Forecasting (TSF) emerged from the Artificial Intelligence... more Alternative approaches for Time Series Forecasting (TSF) emerged from the Artificial Intelligence arena, where optimization algorithms inspired on natural selection processes, such as Genetic Algorithms (GAs) are popular. The present work reports on a two-level architecture, where a (meta-level) binary GA will search for the best TSF model, being the parameters optimized by a (low-level) GA, which encodes real values.
Abstract Jet Grouting (JG) is a Geotechnical Engineering technique that is characterized by a gre... more Abstract Jet Grouting (JG) is a Geotechnical Engineering technique that is characterized by a great versatility, being the best solution for several soil treatment improvement problems. However, JG lacks design rules and quality control. As the result, the main JG works are planned from empirical rules that are often too conservative.
A number of Traffic Engineering (TE) approaches have been recently proposed to improve the perfor... more A number of Traffic Engineering (TE) approaches have been recently proposed to improve the performance of network routing protocols, both developed over MPLS and intra-domain protocols such as OSPF. In this work, a TE approach is proposed for routing optimization in scenarios where unicast and multicast demands are simultaneously present. Evolutionary Algorithms are used as the optimization engine with overall network congestion as the objective function.
Scholarly communication describes the process of sharing and publishing of research findings. Thi... more Scholarly communication describes the process of sharing and publishing of research findings. This report provides some useful guidelines for improving a key scholarly communication aspect: the writing of scientific documents (eg journal articles, conference papers, Doctor of Philosophy thesis).
Abstract This paper quantifies the impact of topological characteristics on the performance of si... more Abstract This paper quantifies the impact of topological characteristics on the performance of single radio multichannel IEEE 802.11 mesh networks. Topological characteristics are the number of nodes per subnetwork, the hop count, the neighbor node density, the hidden nodes, the number of nodes in the neighborhood of the gateway, and the hidden nodes in the neighborhood of the gateway. Network performance metrics are throughput, fairness and delay.
Sometimes, the soil foundation is inadequate for constructions purpose (soft-soils). In these cas... more Sometimes, the soil foundation is inadequate for constructions purpose (soft-soils). In these cases there is need to improve its mechanical and physical properties. For this purpose, there are several geotechnical techniques where Jet Grouting (JG) is highlighted. In many geotechnical structures, advance design incorporates the ultimate limit state (ULS) and the serviceability limit state (SLS) design criteria, for which uniaxial compressive strength and deformability properties of the improved soils are needed.
Strength and stiffness are the mechanical properties currently used in geotechnical works design,... more Strength and stiffness are the mechanical properties currently used in geotechnical works design, namely in jet grouting (JG) treatments. However, when working with this soil improvement technology, due to its inherent geological complexity and high number of variables involved, such design is a hard, perhaps very hard task.
O serviço de correio electrónico assume uma crescente importância na sociedade actual e, em parti... more O serviço de correio electrónico assume uma crescente importância na sociedade actual e, em particular, no âmbito dos serviços de comunicação que hoje em dia são alvo preferencial de utilização por parte dos utilizadores da Internet. No entanto, são ainda muitos os desafios que se colocam a este serviço, nomeadamente no que diz respeito à crescente proliferação do fenómeno de correio electrónico não solicitado.
To increase effectiveness in their marketing and Customer Relationship Manager activities, many o... more To increase effectiveness in their marketing and Customer Relationship Manager activities, many organizations are adopting strategies of Database Marketing (DBM). Nowadays, DBM faces new challenges in business knowledge since current strategies are mainly approached by classical statistical inference, which may fail when complex, multi-dimensional and incomplete data is available.
Forecasting Internet traffic is receiving an increasing attention from the computer networks doma... more Forecasting Internet traffic is receiving an increasing attention from the computer networks domain. Indeed, by improving this task efficient traffic engineering and anomaly detection tools can be developed, leading to economic gains due to better resource management. This paper presents a Neural Network (NN) approach to predict TCP/IP traffic for all links of a backbone network, using both univariate and multivariate strategies.
Certification and quality assessment are crucial issues within the wine industry. Currently, wine... more Certification and quality assessment are crucial issues within the wine industry. Currently, wine quality is mostly assessed by physicochemical (eg alcohol levels) and sensory (eg human expert evaluation) tests. In this paper, we propose a data mining approach to predict wine preferences that is based on easily available analytical tests at the certification step. A large dataset is considered with white vinho verde samples from the Minho region of Portugal.
Classical Machine Learning methods are usually developed to work in static data sets. Yet, real w... more Classical Machine Learning methods are usually developed to work in static data sets. Yet, real world data typically changes over time and there is the need to develop novel adaptive learning algorithms. In this work, a number of algorithms, combining Neural Network learning models and Evolutionary Computation optimization techniques, are compared, being held several simulations based on artificial and real world problems.
This paper addresses the problem of automatic detection and prediction of abnormal human behaviou... more This paper addresses the problem of automatic detection and prediction of abnormal human behaviours in public spaces. For this propose a novel classifier, called N-ary trees, is presented. The classifier processes time series of attributes like the object position, velocity, perimeter and area, to infer the type of action performed. This innovative classifier can detect three types of events: normal; unusual; or abnormal events.
This article presents three methods to forecast accurately the amount of traffic in TCP= IP based... more This article presents three methods to forecast accurately the amount of traffic in TCP= IP based networks: a novel neural network ensemble approach and two important adapted time series methods (ARIMA and Holt-Winters). In order to assess their accuracy, several experiments were held using real-world data from two large Internet service providers. In addition, different time scales (5min, 1h and 1 day) and distinct forecasting lookaheads were analysed.
This paper introduces the INTCare system, an intelligent decision support system for intensive me... more This paper introduces the INTCare system, an intelligent decision support system for intensive medicine. The system aims at the automation of the Knowledge Discovery Process by using autonomous agents that are responsible for the various constituent steps. The system enables automation of data acquisition and model updating avoiding human intervention. We present the first impressions after the deployment of INTCare in a real environment (Intensive Care Unit of the Hospital de Santo António, Oporto, Portugal) where it is supporting the physicians' decisions by means of prognostic Data Mining models. In particular, these techniques are used to predict organ failure and mortality assessment. The main intention is to change the current reactive behaviour to a pro-active one, enhancing the Quality of Service.
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Papers by Paulo Cortez