University of Peloponnese

About: University of Peloponnese is a education organization based out in Tripoli, Greece. It is known for research contribution in the topics: European union & Fading. The organization has 1009 authors who have published 2945 publications receiving 40512 citations.

Machine learning: a review of classification and combining techniques

Abstract: Supervised classification is one of the tasks most frequently carried out by so-called Intelligent Systems. Thus, a large number of techniques have been developed based on Artificial Intelligence (Logic-based techniques, Perceptron-based techniques) and Statistics (Bayesian Networks, Instance-based techniques). The goal of supervised learning is to build a concise model of the distribution of class labels in terms of predictor features. The resulting classifier is then used to assign class labels to the testing instances where the values of the predictor features are known, but the value of the class label is unknown. This paper describes various classification algorithms and the recent attempt for improving classification accuracy--ensembles of classifiers.

DIANA-TarBase v8: a decade-long collection of experimentally supported miRNA-gene interactions.

Abstract: DIANA-TarBase v8 (http://www.microrna.gr/tarbase) is a reference database devoted to the indexing of experimentally supported microRNA (miRNA) targets. Its eighth version is the first database indexing >1 million entries, corresponding to ∼670 000 unique miRNA-target pairs. The interactions are supported by >33 experimental methodologies, applied to ∼600 cell types/tissues under ∼451 experimental conditions. It integrates information on cell-type specific miRNA-gene regulation, while hundreds of thousands of miRNA-binding locations are reported. TarBase is coming of age, with more than a decade of continuous support in the non-coding RNA field. A new module has been implemented that enables the browsing of interactions through different filtering combinations. It permits easy retrieval of positive and negative miRNA targets per species, methodology, cell type and tissue. An incorporated ranking system is utilized for the display of interactions based on the robustness of their supporting methodologies. Statistics, pie-charts and interactive bar-plots depicting the database content are available through a dedicated result page. An intuitive interface is introduced, providing a user-friendly application with flexible options to different queries.

Ontology visualization methods—a survey

Abstract: Ontologies, as sets of concepts and their interrelations in a specific domain, have proven to be a useful tool in the areas of digital libraries, the semantic web, and personalized information management. As a result, there is a growing need for effective ontology visualization for design, management and browsing. There exist several ontology visualization methods and also a number of techniques used in other contexts that could be adapted for ontology representation. The purpose of this article is to present these techniques and categorize their characteristics and features in order to assist method selection and promote future research in the area of ontology visualization.

Relationship quality: a critical literature review and research agenda

Abstract: Purpose – In today's highly competitive environment losing customers is very costly. Customer retention and loyalty have become possible through the development of long‐term, mutually beneficial relationships with customers. This paper seeks to critically review the literature on relationship quality (RQ) and to suggest avenues for further research.Design/methodology/approach – Data were collected with impartial cross‐referencing of papers published in all major journals in the marketing area. Papers are presented in tabulated form based on six rigorously cross‐checked categories of information.Findings – Most RQ research centres on business‐to‐business (b‐to‐b) markets and products use survey data, look at relationships from the customer perspective and analyse either the US or European markets. Also, results differ in various contexts and there is no universally accepted framework for RQ. By analysing the different variables used in previous studies, a general conceptual framework is provided for the st...

Supervised Machine Learning: A Review of Classification Techniques

Abstract: The goal of supervised learning is to build a concise model of the distribution of class labels in terms of predictor features. The resulting classifier is then used to assign class labels to the testing instances where the values of the predictor features are known, but the value of the class label is unknown. This paper describes various supervised machine learning classification techniques. Of course, a single chapter cannot be a complete review of all supervised machine learning classification algorithms (also known induction classification algorithms), yet we hope that the references cited will cover the major theoretical issues, guiding the researcher in interesting research directions and suggesting possible bias combinations that have yet to be explored.