Martin Víta

Fuzzy t-filters and their properties

Abstract Fuzzification of special types of filters on several different algebras of many-valued logics has been very popular in recent years. The main aim of this paper is to point out some general principles concerning particular results about fuzzification of special types of filters. We introduce the notion of a fuzzy t-filter which generalizes most types of special fuzzy filters (e.g. fuzzy implicative, fuzzy boolean, fuzzy fantastic, etc.) and prove some basic properties of fuzzy t -filters.

Curriculum Mapping with Academic Analytics in Medical and Healthcare Education.

Background No universal solution, based on an approved pedagogical approach, exists to parametrically describe, effectively manage, and clearly visualize a higher education institution’s curriculum, including tools for unveiling relationships inside curricular datasets. Objective We aim to solve the issue of medical curriculum mapping to improve understanding of the complex structure and content of medical education programs. Our effort is based on the long-term development and implementation of an original web-based platform, which supports an outcomes-based approach to medical and healthcare education and is suitable for repeated updates and adoption to curriculum innovations. Methods We adopted data exploration and visualization approaches in the context of medical curriculum innovations in higher education institutions domain. We have developed a robust platform, covering detailed formal metadata specifications down to the level of learning units, interconnections, and learning outcomes, in accordance with Bloom’s taxonomy and direct links to a particular biomedical nomenclature. Furthermore, we used selected modeling techniques and data mining methods to generate academic analytics reports from medical curriculum mapping datasets. Results We present a solution that allows users to effectively optimize a curriculum structure that is described with appropriate metadata, such as course attributes, learning units and outcomes, a standardized vocabulary nomenclature, and a tree structure of essential terms. We present a case study implementation that includes effective support for curriculum reengineering efforts of academics through a comprehensive overview of the General Medicine study program. Moreover, we introduce deep content analysis of a dataset that was captured with the use of the curriculum mapping platform; this may assist in detecting any potentially problematic areas, and hence it may help to construct a comprehensive overview for the subsequent global in-depth medical curriculum inspection. Conclusions We have proposed, developed, and implemented an original framework for medical and healthcare curriculum innovations and harmonization, including: planning model, mapping model, and selected academic analytics extracted with the use of data mining.

A short note on t-filters, I -filters and extended filters on residuated lattices

The notion of a t-filter on residuated lattices was introduced in order to generalize a big amount of particular results about special types of filters (e.g. implicative, positive implicative, fantastic etc.). In this short note we are going to point out the relationship between t-filters and I -filters and also between t-filters and extended filters on residuated lattices.

Word2vec based system for recognizing partial textual entailment

Recognizing textual entailment is typically considered as a binary decision task - whether a text T entails a hypothesis H. Thus, in case of a negative answer, it is not possible to express that H is “almost entailed” by T. Partial textual entailment provides one possible approach to this issue. This paper presents an attempt to use word2vec model for recognizing partial (faceted) textual entailment. The proposed approach does not rely on language dependent NLP tools and other linguistic resources, therefore it can be easily implemented in different language environments where word2vec models are available.

Automatic keyword extraction from medical and healthcare curriculum

Medical and healthcare study programmes are quite complicated in terms of branched structure and heterogeneous content. In logical sequence a lot of requirements and demands placed on students appear there. This paper focuses on an innovative way how to discover and understand complex curricula using modern information and communication technologies. We introduce an algorithm for curriculum metadata automatic processing - automatic keyword extraction based on unsupervised approaches, and we demonstrate a real application during a process of innovation and optimization of medical education. The outputs of our pilot analysis represent systematic description of medical curriculum by three different approaches (centrality measures) used for relevant keywords extraction. Further evaluation by senior curriculum designers and guarantors is required to obtain an objective benchmark.

Exploring medical curricula using social network analysis methods

This contribution demonstrates how to apply concepts of social network analysis on educational data. The main aim of this approach is to provide a deeper insight into the structure of courses and/or other learning units that belong to a given curriculum in order to improve the learning process. The presented work can help us discover communities of similar study disciplines (based on the similarity measures of textual descriptions of their contents), as well as identify important courses strongly linked to others, and also find more independent and less important parts of the curriculum using centrality measures arising from the graph theory and social network analysis.

Generic Private Social Network for Knowledge Management

The main motivation of this paper is a support of knowledge management for small to medium enterprises business. We present our tool sitIT.cz which was developed to support communication of IT specialists both from academia and business using public funding. The main message of this paper is that this tool is quite generic and can be used in different scenarios. Particularly significant is its use as a private social network for knowledge management in a company. Our system is quite rich on actors, knowledge classification schemes, search functionalities, and trust management.