Improving Ontology Recommendation and Reuse in WebCORE by Collaborative Assessments

In this work, we present an extension of CORE [8], a tool for Collaborative Ontology Reuse and Evaluation. The system receives an informal description of a specific semantic domain and determines which ontologies from a repository are the most appropriate to describe the given domain. For this task, the environment is divided into three modules. The first component receives the problem description as a set of terms, and allows the user to refine and enlarge it using WordNet. The second module applies multiple automatic criteria to evaluate the ontologies of the repository, and determines which ones fit best the problem description. A ranked list of ontologies is returned for each criterion, and the lists are combined by means of rank fusion techniques. Finally, the third component uses manual user evaluations in order to incorporate a human, collaborative assessment of the ontologies. The new version of the system incorporates several novelties, such as its implementation as a web application; the incorporation of a NLP module to manage the problem definitions; modifications on the automatic ontology retrieval strategies; and a collaborative framework to find potential relevant terms according to previous user queries. Finally, we present some early experiments on ontology retrieval and evaluation, showing the benefits of our system

Development of the Information Society in Czech Republic, Poland and Slovakia

The article is presenting facts about the politics carried on the EU concerning development of the information society in Czech Republic, Poland and Slovakia - countries that in 2004 became members of the EU. Enlargement of the EU structures allowed for more dynamic development of these countries in the information society context. The situation of each country was presented by indicators describing the household and the community situation in information society. Indicators was gained from Eurostat system. The universality of these indicators lets to the assessment of the level and dynamics of development in relation to the EU average. Comparison of Poland and its southern neighbors allows also to observe changes that occur and may allow better progress in this field.Artykul prezentuje dane na temat prowadzonej w UE polityki w zakresie rozwoju spoleczeństwa informacyjnego w Czechach, Polsce i Slowacji, które staly się czlonkami UE w 2004 roku. Rozszerzenie struktur unijnych pozwolilo na zdynamizowanie rozwoju tych krajów w zakresie spoleczeństwa informacyjnego. Sytuację poszczególnych krajów zaprezentowano przy pomocy wskażników opisujących gospodarstwa domowe oraz spoleczność pochodzące z Eurostatu. Powszechność tych wskażników pozwala na ocenę dynamiki rozwoju oraz poziomu tego rozwoju w odniesieniu do wartości średniej w UE. Porównanie Polski oraz jej poludniowych sąsiadów pozwolić ma również na dostrzeżenie przemian, które zachodzą i mogą pozwolić na lepszy postęp w tej dziedzinie

Energy performance forecasting of residential buildings using fuzzy approaches

The energy consumption used for domestic purposes in Europe is, to a considerable extent, due to heating and cooling. This energy is produced mostly by burning fossil fuels, which has a high negative environmental impact. The characteristics of a building are an important factor to determine the necessities of heating and cooling loads. Therefore, the study of the relevant characteristics of the buildings, regarding the heating and cooling needed to maintain comfortable indoor air conditions, could be very useful in order to design and construct energy-efficient buildings. In previous studies, different machine-learning approaches have been used to predict heating and cooling loads from the set of variables: relative compactness, surface area, wall area, roof area, overall height, orientation, glazing area and glazing area distribution. However, none of these methods are based on fuzzy logic. In this research, we study two fuzzy logic approaches, i.e., fuzzy inductive reasoning (FIR) and adaptive neuro fuzzy inference system (ANFIS), to deal with the same problem. Fuzzy approaches obtain very good results, outperforming all the methods described in previous studies except one. In this work, we also study the feature selection process of FIR methodology as a pre-processing tool to select the more relevant variables before the use of any predictive modelling methodology. It is proven that FIR feature selection provides interesting insights into the main building variables causally related to heating and cooling loads. This allows better decision making and design strategies, since accurate cooling and heating load estimations and correct identification of parameters that affect building energy demands are of high importance to optimize building designs and equipment specifications.Peer ReviewedPostprint (published version

Communication practices of the Karen in Sheffield: Seeking to navigate their three zones of displacement

This study investigates communication practices of a newly arrived Karen refugee community in the UK who, as well as establishing themselves in a strange country, seek to keep in touch, campaign politically and maintain identity collectively through communication and contact with their global diaspora. We look at the technologies, motivations and inhibiting factors applying to the communication by adult members of this community and construct the idea of three zones of displacement which help to model the particular contexts, challenges and methods of their communication. We find that overall, they are using a wide range of internet-based technologies, with the aim to 'keep-in-touch' (personal contacts) and to 'spread the word' (political communication). This also includes archaic, traditional and hybrid methods to achieve extended communication with contacts in other 'zones'. We also identify the importance of the notion of ‘village’ as metaphor and entity in their conceptualisation of diasporic and local community cohesion. We identify the key inhibitors to their communication as cost, education, literacy and age. Finally, we speculate on the uncertain outcomes of their approach to digital media in achieving their political aims

Modeling the thermal behavior of biosphere 2 in a non-controlled environment using bond graphs

Biosphere 2 is a closed ecological system of high complexity built to deepen the understanding of ecological systems, to study the dynamics of closed ecologies, and to learn to control their behavior. The use of modeling and simulation is crucial in the achievement of these goals. Understanding a physical system is almost synonymous with possessing a model of its comportment. The main goal of this study is the development of a dynamic bond graph model that represents the thermal behavior of the complex ecological system under study, Biosphere 2. In this work, a first model that captures the behavior of the ecological system in a non-controlled environment is presented.Postprint (published version

Automatic construction of rules fuzzy for modelling and prediction of the central nervous system

The main goal of this work is to study the performance of CARFIR (Automatic Construction of Rules in Fuzzy Inductive Reasoning) methodology for the modelling and prediction of the human central nervous system (CNS). The CNS controls the hemodynamical system by generating the regulating signals for the blood vessels and the heart. The main idea behind CARFIR is to expand the capacity of the FIR methodology allowing it to work with classical fuzzy rules. CARFIR is able to automatically construct fuzzy rules starting from a set of pattern rules obtained by FIR. The new methodology preserves as much as possible the knowledge of the pattern rules in a compact fuzzy rule base. The prediction results obtained by the fuzzy prediction process of CARFIR methodology are compared with those of other inductive methodologies, i.e. FIR, NARMAX and neural networksPostprint (published version

Personalized content retrieval in context using ontological knowledge

Personalized content retrieval aims at improving the retrieval process by taking into account the particular interests of individual users. However, not all user preferences are relevant in all situations. It is well known that human preferences are complex, multiple, heterogeneous, changing, even contradictory, and should be understood in context with the user goals and tasks at hand. In this paper, we propose a method to build a dynamic representation of the semantic context of ongoing retrieval tasks, which is used to activate different subsets of user interests at runtime, in a way that out-of-context preferences are discarded. Our approach is based on an ontology-driven representation of the domain of discourse, providing enriched descriptions of the semantics involved in retrieval actions and preferences, and enabling the definition of effective means to relate preferences and context

Intelligent data analysis approaches to churn as a business problem: a survey

Globalization processes and market deregulation policies are rapidly changing the competitive environments of many economic sectors. The appearance of new competitors and technologies leads to an increase in competition and, with it, a growing preoccupation among service-providing companies with creating stronger customer bonds. In this context, anticipating the customer’s intention to abandon the provider, a phenomenon known as churn, becomes a competitive advantage. Such anticipation can be the result of the correct application of information-based knowledge extraction in the form of business analytics. In particular, the use of intelligent data analysis, or data mining, for the analysis of market surveyed information can be of great assistance to churn management. In this paper, we provide a detailed survey of recent applications of business analytics to churn, with a focus on computational intelligence methods. This is preceded by an in-depth discussion of churn within the context of customer continuity management. The survey is structured according to the stages identified as basic for the building of the predictive models of churn, as well as according to the different types of predictive methods employed and the business areas of their application.Peer ReviewedPostprint (author's final draft

Feature selection algorithms: a survey and experimental evaluation

In view of the substantial number of existing feature selection algorithms, the need arises to count on criteria that enables to adequately decide which algorithm to use in certain situations. This work reviews several fundamental algorithms found in the literature and assesses their performance in a controlled scenario. A scoring measure ranks the algorithms by taking into account the amount of relevance, irrelevance and redundance on sample data sets. This measure computes the degree of matching between the output given by the algorithm and the known optimal solution. Sample size effects are also studied.Postprint (published version