Zobrazeno 1 - 10
of 171
pro vyhledávání: '"Martin Atzmueller"'
Publikováno v:
Applied Network Science, Vol 6, Iss 1, Pp 1-24 (2021)
Abstract Complex networks lend themselves for the modeling of multidimensional data, such as relational and/or temporal data. In particular, when such complex data and their inherent relationships need to be formalized, complex network modeling and i
Externí odkaz:
https://doaj.org/article/79e7be8082854849b4baf53a14311bef
Publikováno v:
Data, Vol 8, Iss 3, p 45 (2023)
There has recently been an increasing interest in Learning Management Systems (LMSs). It is currently unclear, however, exactly how these systems are perceived by their users. This article analyzes data on user acceptance for two LMSs (Blackboard and
Externí odkaz:
https://doaj.org/article/986af2993e2949a682eff02fba9e0492
Publikováno v:
Sensors, Vol 22, Iss 21, p 8419 (2022)
Global Navigation Satellite Systems provide autonomous vehicles with precise position information through the process of position augmentation. This paper presents a series of performance tests aimed to compare the position accuracy of augmentation t
Externí odkaz:
https://doaj.org/article/2478df3cfa3b4f46b84d46468ec9a587
Publikováno v:
Applied Network Science, Vol 4, Iss 1, Pp 1-33 (2019)
Abstract Local pattern mining on attributed networks is an important and interesting research area combining ideas from network analysis and data mining. In particular, local patterns on attributed networks allow both the characterization in terms of
Externí odkaz:
https://doaj.org/article/ee8bc22c49a24389ac8ed2217c2a6ab4
Autor:
Roberto Interdonato, Martin Atzmueller, Sabrina Gaito, Rushed Kanawati, Christine Largeron, Alessandra Sala
Publikováno v:
Applied Network Science, Vol 4, Iss 1, Pp 1-13 (2019)
Abstract The growing availability of multirelational data gives rise to an opportunity for novel characterization of complex real-world relations, supporting the proliferation of diverse network models such as Attributed Graphs, Heterogeneous Network
Externí odkaz:
https://doaj.org/article/a11a6b14b25f4a9fadbf66d6dd46b7e0
Publikováno v:
Applied Sciences, Vol 11, Iss 23, p 11429 (2021)
With the developments in improved computation power and the vast amount of (automatic) data collection, industry has become more data-driven. These data-driven approaches for monitoring processes and machinery require different modeling methods focus
Externí odkaz:
https://doaj.org/article/89cd12647b90461b9da8ed2ee88d23fc
Publikováno v:
Sensors, Vol 21, Iss 13, p 4322 (2021)
Mining ubiquitous sensing data is important but also challenging, due to many factors, such as heterogeneous large-scale data that is often at various levels of abstraction. This also relates particularly to the important aspects of the explainabilit
Externí odkaz:
https://doaj.org/article/eb3e34cd7f424fe99ea7f089c5d0970f
Autor:
Asep Maulana, Martin Atzmueller
Publikováno v:
Applied Sciences, Vol 11, Iss 9, p 4005 (2021)
Anomaly detection in complex networks is an important and challenging task in many application domains. Examples include analysis and sensemaking in human interactions, e.g., in (social) interaction networks, as well as the analysis of the behavior o
Externí odkaz:
https://doaj.org/article/d320ef873bf846579abb49087fe986f1
Autor:
Martin Atzmueller
Publikováno v:
Journal of Data Mining and Digital Humanities, Vol 2014 (2014)
Social media and social networks have already woven themselves into the very fabric of everyday life. This results in a dramatic increase of social data capturing various relations between the users and their associated artifacts, both in online netw
Externí odkaz:
https://doaj.org/article/490e126a5a31455a9219d491ead616b9
Publikováno v:
European Interdisciplinary Cybersecurity Conference.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9a8c73e0bc2b7223db8689a7de724e2e
https://doi.org/10.1145/3590777.3590803
https://doi.org/10.1145/3590777.3590803