SwePub - search: WFRF:(Atzmueller Martin)

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1.	Atzmueller, Martin, et al. (author) International Workshop on Mining Attributed Networks (MATNET 2018) Chairs' Welcome 2018 In: WWW '18. - New York, New York, USA : Association for Computing Machinery (ACM). - 9781450356404 ; , s. 1231-1233 Conference paper (other academic/artistic)abstract Attributed network models have seen an increasing success in recent years, thanks to their informative power and to their ability to model complex networked relations that characterize most real-world phenomena. Their use has been attractive to communities in different disciplines such as computer science, physics, social science, as well as in interdisciplinary research environments. The use of such models has been also supported by the increasing easiness in collecting multirelational data from the Web, e.g., from online social media platforms, crowdsourced data, online knowledge bases; within this view, the World Wide Web is an inestimable source of information, which can be conveniently represented with feature-rich network models, e.g., enclosing temporal aspects of the data, quantitative and/or qualitative properties of nodes, different relations between a common set of entities, different existence probabilities, or modeling connection between different entity types.

Atzmueller, Martin, et al. (author)
International Workshop on Mining Attributed Networks (MATNET 2018) Chairs' Welcome
2018
In: WWW '18. - New York, New York, USA : Association for Computing Machinery (ACM). - 9781450356404 ; , s. 1231-1233
Conference paper (other academic/artistic)abstract
- Attributed network models have seen an increasing success in recent years, thanks to their informative power and to their ability to model complex networked relations that characterize most real-world phenomena. Their use has been attractive to communities in different disciplines such as computer science, physics, social science, as well as in interdisciplinary research environments. The use of such models has been also supported by the increasing easiness in collecting multirelational data from the Web, e.g., from online social media platforms, crowdsourced data, online knowledge bases; within this view, the World Wide Web is an inestimable source of information, which can be conveniently represented with feature-rich network models, e.g., enclosing temporal aspects of the data, quantitative and/or qualitative properties of nodes, different relations between a common set of entities, different existence probabilities, or modeling connection between different entity types.

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