Zobrazeno 1 - 10
of 95
pro vyhledávání: '"Christian Sacarea"'
Publikováno v:
Journal of Communications Software and Systems, Vol 17, Iss 1, Pp 29-35 (2021)
In this paper we propose an approach for classifying documents, embedding documents into feature vectors and using these embeddings for finding similarities between them. Our chosen domain for applying this method is the IT-Service Support branch, wh
Externí odkaz:
https://doaj.org/article/a15eff5d56c04a0bab0ddc1cc2ae3b20
Autor:
Cristian Tufisi, Catalin V. Rusu, Nicoleta Gillich, Marius Vasile Pop, Codruta Oana Hamat, Christian Sacarea, Gilbert-Rainer Gillich
Publikováno v:
Applied Sciences, Vol 12, Iss 14, p 7231 (2022)
Evaluating the integrity of structures is an important issue in engineering applications. The use of vibration-based techniques has become a common approach to assessing cracks, which are the most frequently occurring damage in structures. When invol
Externí odkaz:
https://doaj.org/article/e3465462bb2e4617972e585b9324c729
Autor:
Nicoleta Gillich, Cristian Tufisi, Christian Sacarea, Catalin V. Rusu, Gilbert-Rainer Gillich, Zeno-Iosif Praisach, Mario Ardeljan
Publikováno v:
Sensors, Vol 22, Iss 3, p 1118 (2022)
Damage detection based on modal parameter changes has become popular in the last few decades. Nowadays, there are robust and reliable mathematical relations available to predict natural frequency changes if damage parameters are known. Using these re
Externí odkaz:
https://doaj.org/article/a8fd4982ddc64ec4bd891b18c26a97b6
Publikováno v:
Journal of Communications Software and Systems, Vol 17, Iss 1, Pp 29-35 (2021)
Journal of Communications Software and Systems
Volume 17
Issue 1
Journal of Communications Software and Systems
Volume 17
Issue 1
Natural language processing (NLP) is a branch of computer science concerned with the understanding of human language and communication, and translating these into a computer-comprehensible embedding. Our goal in this paper is to capture meaning from
Publikováno v:
Studia Universitatis Babes-Bolyai Matematica. 64:11-23
Boolean Concept Logic has been introduced by R. Wille as a mathematical theory based on Formal Concept Analysis. Concept lattices are extended with two new operations, negation and opposition which then lead to algebras of protoconcepts which are equ
Publikováno v:
SoftCOM
MongoDB document store is the most popular of NoSQL systems. For managing and retrieving data, having a representation of its inherent knowledge structures proves to be significant for modeling purposes. In this paper, we present a modeling method fo
Publikováno v:
SYNASC
Formal Concept Analysis (FCA) is a prominent research field having its roots in applied mathematics. Based on a mathematization of concepts and their hierarchies, FCA and its varieties have the potential to unify knowledge discovery methodologies. Th
Publikováno v:
SYNASC
Formal Concept Analysis (FCA) is a prominent field of Applied Mathematics grounded on the formalization of the notions of concept and concept hierarchy. Based on the expressive power of the graphical representation of knowledge clusters as order diag
Publikováno v:
Graph-Based Representation and Reasoning ISBN: 9783319913780
ICCS
ICCS
A key ability of human reasoning is analogical reasoning. In this context, an important notion is that of analogical proportions that have been formalized and analyzed in the last decade. A bridging to Formal Concept Analysis (FCA) has been brought b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::be3e3bda044c5db4e19f7a1e7d14c73b
https://doi.org/10.1007/978-3-319-91379-7_2
https://doi.org/10.1007/978-3-319-91379-7_2
Publikováno v:
Graph-Based Representation and Reasoning ISBN: 9783319913780
ICCS
ICCS
Due to the fast growing of data in the digital world, not only in volume but also in its variety (structured, un-structured or hybrid), traditional RDBMS are complemented with a rich set of systems, known as NoSQL. One of the main categories of NoSQL
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9d68d5771483e2281ddb33ee39e6b38e
https://doi.org/10.1007/978-3-319-91379-7_13
https://doi.org/10.1007/978-3-319-91379-7_13