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001-es BibID:	BIBFORM095567
035-os BibID:	(cikkazonosító)852 (WoS)000676479300001 (Scopus)85109815317
Első szerző:	Aszalós László (matematikus)
Cím:	Decompose Boolean Matrices with Correlation Clustering / László Aszalós
Dátum:	2021
ISSN:	1099-4300
Megjegyzések:	One of the tasks of data science is the decomposition of large matrices in order to understand their structures. A special case of this is when we decompose relations, i.e., logical matrices. In this paper, we present a method based on the similarity of rows and columns, which uses correlation clustering to cluster the rows and columns of the matrix, facilitating the visualization of the relation by rearranging the rows and columns. In this article, we compare our method with Gunther Schmidt's problems and solutions. Our method produces the original solutions by selecting its parameters from a small set. However, with other parameters, it provides solutions with even lower entropy.
Tárgyszavak:	Műszaki tudományok Informatikai tudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk matrix decomposition correlation clustering similarity
Megjelenés:	Entropy. - 23 : 7 (2021), p. 1-12. -
Pályázati támogatás:	EFOP-3.6.3-VEKOP-16-2017-00002 EFOP
Internet cím:	Szerző által megadott URL DOI Intézményi repozitóriumban (DEA) tárolt változat
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001-es BibID:	BIBFORM115191
035-os BibID:	(WOS)000872667200001 (Scopus)85140615847
Első szerző:	Csernoch Mária (informatika tanár)
Cím:	The Interpretation of Graphical Information in Word Processing / Mária Csernoch, János Máth, Tímea Nagy
Dátum:	2022
ISSN:	1099-4300
Megjegyzések:	Word processing is one of the most popular digital activities. Despite its popularity, it is haunted by false assumptions, misconceptions, and ineffective and inefficient practices leading to erroneous digital text-based documents. The focus of the present paper is automated numbering and distinguishing between manual and automated numbering. In general, one bit of information on the GUI-the position of the cursor-is enough to tell whether a numbering is manual or automated. To decide how much information must be put on the channel-the teaching-learning process-in order to reach end-users, we designed and implemented a method that includes the analysis of teaching, learning, tutorial, and testing sources, the collection and analysis of Word documents shared on the internet or in closed groups, the testing of grade 7-10 students` knowledge in automated numbering, and calculating the entropy of automated numbering. The combination of the test results and the semantics of the automated numbering was used to measure the entropy of automated numbering. It was found that to transfer one bit of information on the GUI, at least three bits of information must be transferred during the teaching-learning process. Furthermore, it was revealed that the information connected to numbering is not the pure use of tools, but the semantics of this feature put into a real-world context.
Tárgyszavak:	idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk wordprocessing cursor automatednumbering GUI entropy redundancy
Megjelenés:	Entropy. - 24 : 10 (2022), p. 1-16. -
További szerzők:	Máth János (1959-) (matematikus) Nagy Tímea Katalin (1995-) (informatika-matematika tanár)
Pályázati támogatás:	KDP-2021 Egyéb
Internet cím:	Szerző által megadott URL DOI Intézményi repozitóriumban (DEA) tárolt változat
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001-es BibID:	BIBFORM113371
035-os BibID:	(WOS)000939164600001 (Scopus)85148938983 (Cikkazonosító)302
Első szerző:	Csernoch Mária (informatika tanár)
Cím:	The Entropy of Digital Texts - The Mathematical Background of Correctness / Mária Csernoch, Keve Nagy, Tímea Nagy
Dátum:	2023
ISSN:	1099-4300
Megjegyzések:	Based on Shannon's communication theory, in the present paper, we provide the theoretical background to finding an objective measurement-the text-entropy-that can describe the quality of digital natural language documents handled with word processors. The text-entropy can be calculated from the formatting, correction, and modification entropy, and based on these values, we are able to tell how correct or how erroneous digital text-based documents are. To present how the theory can be applied to real-world texts, for the present study, three erroneous MS Word documents were selected. With these examples, we can demonstrate how to build their correcting, formatting, and modification algorithms, to calculate the time spent on modification and the entropy of the completed tasks, in both the original erroneous and the corrected documents. In general, it was found that using and modifying properly edited and formatted digital texts requires less or an equal number of knowledge-items. In information theory, it means that less data must be put on the communication channel than in the case of erroneous documents. The analysis also revealed that in the corrected documents not only the quantity of the data is less, but the quality of the data (knowledge pieces) is higher. As the consequence of these two findings, it is proven that the modification time of erroneous documents is severalfold of the correct ones, even in the case of minimal first level actions. It is also proven that to avoid the repetition of the time- and resource-consuming actions, we must correct the documents before their modification.
Tárgyszavak:	Műszaki tudományok Informatikai tudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk word processing errors correction modification formatting communication entropy text-entropy
Megjelenés:	Entropy. - 25 : 2 (2023), p. 1-34. -
További szerzők:	Nagy Keve (1974-) (mérnökinformatikus) Nagy Tímea Katalin (1995-) (informatika-matematika tanár)
Pályázati támogatás:	NKFI - KDP-2021 Egyéb
Internet cím:	Szerző által megadott URL DOI Intézményi repozitóriumban (DEA) tárolt változat
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