Vitor Basto Fernandes

ISCTE-Instituto Universitário de Lisboa | ISCTE · Department of Information Science and Technology

In this chapter, we present a Many-Criteria Optimisation and Decision Analysis (MACODA) Ontology and MACODA Knowledge Management Web-Based Platform (named MyCODA, available at http://macoda.club) for the research community. The purpose of this initiative is to allow for the collaborative development of an ontology to represent the MACODA knowledge...

When it comes to the need to manage cyber security, identifying and utilising good cyber security metrics is essential. This allows organisations to manage their cyber risk more effectively. However, the literature lacks consensus on properties and characteristics of good metrics. We join the current efforts that aim at closing this gap. Hence, the...

Contemporaneous environments involve a large number of information which is received from many interconnected devices and integrated by many platforms. The Internet of Things and Cloud computing offer services to deal with such big data, so that enterprises can play in their business core by outsourcing the development, the configuration, and the m...

Despite new developments in machine learning classification techniques, improving the accuracy of spam filtering is a difficult task due to linguistic phenomena that limit its effectiveness. In particular, we highlight polysemy, synonymy, the usage of hypernyms/hyponyms, and the presence of irrelevant/confusing words. These problems should be solve...

This article presents an innovative knowledge management approach for the validation and transfer of knowledge between semantic networks or ontologies and a target ontology represented in web ontology language (OWL) format. This process has been designed for addressing the quality improvement of ontologies automatically created by learning techniqu...

Most research into anti-phishing defence assumes that the mal-actor is attempting to harvest end-users' personally identifiable information or login credentials and, hence, focuses on detecting phishing websites. The defences for this type of attack are usually activated after the end-user clicks on a link, at which point the link is checked. This...

Due to large volumes of data from Cloud Computing and from the Internet of Things, the ompanies’ software ecosystem requires an efficient integration of applications and services. Performance improvement from integration platforms’ runtime systems is directly related to task scheduling strategies from integration processes. It is still a challenge...

Growing demand for reduced local hardware infrastructure is driving the adoption of Cloud Computing. In the Infrastructure-as-a-Service model, service providers offer virtualized computational resources in the form of virtual machine instances. The existence of a large variety of providers and instances makes the decision-making process a difficult...

The need for integration of applications and services in business processes from enterprises has increased with the advancement of cloud and mobile applications. Enterprises started dealing with high volumes of data from the cloud and from mobile applications, besides their own. This is the reason why integration tools must adapt themselves to hand...

Enterprises have a set of applications support that needs to work synchronouslyand efficiently to respond quickly to business processes. To achieve high performance in theexecution of the applications, software engineers suitably must use task scheduling on thecomputational resources. The round robin algorithm is an efficient and effective scheduli...

Enterprises have a set of applications support that needs to work synchronouslyand efficiently to respond quickly to business processes. To achieve high performance in theexecution of the applications, software engineers suitably must use task scheduling on thecomputational resources. The round robin algorithm is an efficient and effective scheduli...

Cloud computing allows enterprises to incorporate applications and computational resources as services, and thus, enterprises can concentrate on their business processes, without concerning the development, configuration and maintenance of these applications and resources. Integration platforms are one of these services that allow enterprises to in...

Companies' software ecosystem-composed of local applications and cloud computing services-is made up by the connection of integration platforms and applications. Run-time systems are arguably the most considerable components for integration platforms performance. Our literature review has identified that most integration run-time systems adopt a gl...

Companies' software ecosystem-composed of local applications and cloud computing services-is made up by the connection of integration platforms and applications. Run-time systems are arguably the most considerable components for integration platforms performance. Our literature review has identified that most integration run-time systems adopt a gl...

Ontology-learning methods were introduced in the knowledge engineering area to automatically build ontologies from natural language texts related to a domain. Despite the initial appeal of these methods, automatically generated ontologies may have errors, inconsistencies, and a poor design quality, all of which must be manually fixed, in order to m...

Enterprises have a set of applications support that need to work synchronously and efficiently to respond quickly to business processes. To achieve high performance in the execution of the applications, software engineers suitably must task scheduling on the computational resources. The Round Robin algorithm is an efficient and effective scheduling...

Enterprises have a set of applications support that need to work synchronously and efficiently to respond quickly to business processes. To achieve high performance in the execution of the applications, software engineers suitably must task scheduling on the computational resources. The Round Robin algorithm is an efficient and effective scheduling...

This article addresses major information systems integration problems, approaches, technologies, and tools within the context of Model-Driven Software Engineering. The Guaraná integration platform is introduced as an innovative platform amongst state-of-the-art technologies available for enterprises to design and implement integration solutions. In...

This paper presents OntologyFixer, a web-based tool that supports a methodology to build, assess, and improve the quality of ontology web language (OWL) ontologies. Using our software, knowledge engineers are able to fix low-quality OWL ontologies (such as those created from natural language documents using ontology learning processes). The fixing...

In recent years, most content-based spam filters have been implemented using Machine Learning (ML) approaches by means of token-based representations of textual contents. After introducing multiple performance enhancements, the impact has been virtually irrelevant. Recent studies have introduced synset-based content representations as a reliable wa...

The aim of the current work is to create a mobile application that helps bard singers and guitar players sing the same songs and play the same chords. The development of this software product was conducted under the operating system Android using Java programming languages and Kotlin. SQLite database management system was selected for storing data....

The intelligent system of a smart house, which is designed to create from any house, office, or building a smart room, was created in the overall process. Recent trends in technology development demonstrate that more and more things are being automated around us. Even ordinary things become «smarter» and open a new functional use. This has led to a...

The article describes the peculiarities of linguometry information technologies usage to determine the linguometric coefficients dynamics of the text content authorship. The linguistic and statistical analysis of the author texts within a certain time period takes advantage of the text content-monitoring based on the NLP methods to determine the se...

Machine learning methods have become an indispensable tool for utilizing large knowledge and data repositories in science and technology. In the context of the pharmaceutical domain, the amount of acquired knowledge about the design and synthesis of pharmaceutical agents and bioactive molecules (drugs) is enormous. The primary challenge for automat...

The increasing demand for companies to reduce the IT infrastructure (on-premise) are driving the adoption of a type of cloud computing category known as Infrastructure-as-a-Service (IaaS) to provide virtualized computing resources over the Internet. However, the choice of an instance of virtual machine whose configuration is able to meet the demand...

In the given article content is support method as the content lifecycle stage in Web systems is proposed. The model describes the processes of information resources processing in the electronic business systems and simplifies the content automation support technology. In the given paper the main problems of e-commerce and content function managemen...

In the given article content is support method as the content lifecycle stage in Web systems is proposed. The model describes the processes of information resources processing in the electronic business systems and simplifies the content automation support technology. In the given paper the main problems of e-commerce and content function managemen...

Ensemble learning can improve the performance of individual classifiers by combining their decisions. The sparseness of ensemble learning has attracted much attention in recent years. In this paper, a novel multiobjective sparse ensemble learning (MOSEL) model is proposed. Firstly, to describe the ensemble classifiers more precisely the detection e...

The receiver operating characteristic (ROC) and detection error tradeoff (DET) curves have been widely used in the machine learning community to analyze the performance of classifiers. The area (or volume) under the convex hull has been used as a scalar indicator for the performance of a set of classifiers in ROC and DET space. Recently, 3D convex-...

This paper presents a 4-objective evolutionary multiobjective optimization study for optimizing the error rates (false positives, false negatives), reliability, and complexity of binary classifiers. The example taken is the email anti-spam filtering problem.

At present, a large amount of software has been created to analyze social networks, such as libraries to access online social networking APIs, software to draw graphs and tools to use and analyze networks. In fact, and because of the use of Moodle as standard Learning Management System at the University of Las Palmas de Gran Canaria, in 2009 was bo...

This paper presents an evolutionary multi-objective optimization problem formulation for the anti-spam filtering problem, addressing both the classification quality criteria (False Positive and False Negative error rates) and email messages classification time (minimization). This approach is compared to single objective problem formulations found...

The aim of evolutionary level set approximation is to find a finite representation of a level set of a given black box function. The problem of level set approximation plays a vital role in solving problems, for instance in fault detection in water distribution systems, engineering design, parameter identification in gene regulatory networks, and i...

In this chapter it is discussed, how the concept of diversity plays a crucial role in contemporary (multi-objective) optimization algorithms. It is shown that diversity maintenance can have a different purpose, such as improving global convergence reliability or finding alternative solutions to a (multi-objective) optimization problem. Moreover, di...

User preference integration is of great importance in multi-objective optimization, in particular in many objective optimization. Preferences have long been considered in traditional multicriteria decision making (MCDM) which is based on mathematical programming. Recently, it is integrated in multi-objective metaheuristics (MOMH), resulting in focu...

Integrating user preferences in Evolutionary Multiobjective Optimization (EMO) is currently a prevalent research topic. There is a large variety of preference handling methods (originated from Multicriteria decision making, MCDM) and EMO methods, which have been combined in various ways. This paper proposes a Web Ontology Language (OWL) ontology to...

One of the main advances in information technology today is cloud computing. It is a great alternative for users to reduce costs related to the need to acquire and maintain computational infrastructure to develop, implement and execute software applications. Cloud computing services are offered by providers and can be classified into three main mod...

This paper presents ongoing work of a decision aiding software intended to support cyber risk and cyber threats analysis of an information and communication technology infrastructure. The work is focused on the evaluation of the most popular and relevant tools available for risk assessment and decision making in the cybersecurity domain. Their prop...

To protect a system from potential cyber security breaches and attacks, one needs to select efficient security controls, taking into account technical and institutional goals and constraints, such as available budget, enterprise activity, internal and external environment. Here we model the security controls selection problem as a two-stage decisio...

Classifier performance optimization in machine learning can be stated as a multi-objective optimization problem. In this context, recent works have shown the utility of simple evolutionary multi-objective algorithms (NSGA-II, SPEA2) to conveniently optimize the global performance of different anti-spam filters. The present work extends existing con...

The receiver operating characteristic (ROC) and detection error tradeoff (DET) curves are frequently used in the machine learning community to analyze the performance of binary classifiers. Recently, the convex-hull-based multiobjective genetic programming algorithm was proposed and successfully applied to maximize the convex hull area for binary c...

Today's complex, unstable and competitive society raises several difficulties to organisations. In this context, Information and Communications Technologies (ICT) and information itself have become resources of vital importance. The pressing need for Information Systems (IS) to meet several business requirements, in addition to the complexity invol...

Choosing an optimal investment in information security is an issue most companies face these days. Which security controls to buy to protect the IT system of a company in the best way? Selecting a subset of security controls among many available ones can be seen as a resource allocation problem that should take into account conflicting objectives a...

In this paper we present an Enterprise Application Integration (EAI) based proposal for research outcomes information management. The proposal is contextualized in terms of national and international science and research outcomes information management, corresponding supporting information systems and ecosystems. Information systems interoperabilit...

It is not difficult to find an enterprise which has a software ecosystem composed of applications that were built using different technologies, data models, operating systems, and most often were not designed to exchange data and share functionalities. Enterprise Application Integration provides methodologies and tools to design and implement integ...

This paper introduces RuleSIM, a toolkit comprising different simulation tools specifically designed to aid researchers concerned about spam-filtering throughput. RuleSIM allows easily designing, developing, simulating and comparing new scheduling heuristics using different filters and sets of e-mails. Simulation results can be both graphically ana...

Enterprise application integration concerns with the use of methodologies and tools to design and implement integration solutions to integrate a set of heterogeneous enterprise applications. Amongst the integration technologies to design and implement integration solutions is Guaraná. This technology provides a domain-specific language that enables...

This work presents a conceptual proposal to address the problem of intensive human specialized resources that are nowadays required for the maintenance and optimized operation of digital contents filtering in general and anti-spam filtering in particular. The huge amount of spam, malware, virus, and other illegitimate digital contents distributed t...

Finding a good classifier is a multiobjective optimization problem with different error rates and the costs to be minimized. The receiver operating characteristic is widely used in the machine learning community to analyze the performance of parametric classifiers or sets of Pareto optimal classifiers. In order to directly compare two sets of class...

Today's complex, unstable and competitive society raises several difficulties to organisations. In this context, Information and Communications Technologies (ICT) and information itself have become resources of vital importance. The pressing need for Information Systems (IS) to meet several business requirements, in addition to the complexity invol...

This work is devoted to the problem of optimising scores for anti-spam filters, which is essential for the accuracy of any filter based anti-spam system, and is also one of the biggest challenges in this research area. In particular, this optimisation problem is considered from two different points of view: single and multiobjective problem formula...

The demographic evolution of most western developed countries show a progressive increase on population aged 65 and older. One of the consequences of this gradual ageing is the rise of expensive age-related disabilities. Elder dementia patients often get lost due to temporary lack of a sense of direction. This may put them at risk and cause their f...

Information systems interoperability is a complex topic that needs often to be addressed in a specific way. This paper presents an approach for interoperability between point-of-sales systems in the food sales domain and food composition database systems (food nutritional composition). The aim of this proposal is the creation of an integration mech...

A 50-year-old man was referred to the outpatient colonoscopy clinic after a positive fecal occult blood test during screening for colorectal cancer. Colonoscopy, which was performed with the patient sedated, revealed a 12-mm tumor covered by normal, smooth mucosa at the site of the appendicular orifice. A biopsy was taken, but this led to an immedi...

This work presents recent developments on multi objective evolutionary algorithms, so-called set-based evolutionary algorithms. These techniques are shown to approximate a Pareto front of efficient solutions taking into account both quality of the approximation and its diversity, both important in the design of these methods. Set-based evolutionary...

This work presents a review on evolutionary algorithms when applied to problems with multiple objectives to be optimized simultaneously. Evolutionary algorithms are well-known optimization techniques utilized in situations where exact methods fail, in particular, in case of optimization of complex, non-convex, non-differentiable, non-smooth and/or...