Mapping Evaluation for Semantic Browsing

• Autorzy: Veslava Osinska , Adam Jozwik , Grzegorz Osinski
• Języki publikacji: EN

Abstrakty

EN

The paper contributes to the problem solving in semantic browsing and analysis of scientific articles. With reference to presented visual interface, four - the most popular methods of mapping including own approach - MDS with spherical topology, have been compared. For a comparison quantitative measures were applied which allowed to select the most appropriate mapping way with an accurate reflection of the dynamics of data. For the quantitative analysis the authors used machine learning and pattern recognition algorithms and described: clusterization degree, fractal dimension and lacunarity. Local density differences, clusterization, homogeneity, and gappiness were measured to show the most acceptable layout for an analysis, perception and exploration processes. Visual interface for analysis how computer science evolved through the two last decades is presented on website. Results of both quantitative and qualitative analysis have revealed good convergence.(original abstract)

Słowa kluczowe

EN

Knowledge mapping; Machine learning

PL

Mapowanie wiedzy; Uczenie maszynowe

• Czasopismo: Annals of Computer Science and Information Systems
• Rocznik: 2015
• Tom: 5
• Strony: 329--335

Twórcy

autor

Veslava Osinska

• Institute of Information Science and Book Studies, Nicolaus Copernicus University, Toruń, Poland

autor

Adam Jozwik

• Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Science, Warsaw; Institute of Computer Science, College of Social and Media Culture, Toruń, Poland

autor

Grzegorz Osinski

• Institute of Computer Science, College of Social and Media Culture, Toruń, Poland

Bibliografia

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Identyfikatory

DOI

10.15439/2015F50