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A fully synthetic textual dataset of student learning habits and preferences generated using a large language model. [PDF]

Data Brief
Hasan M.
europepmc   +1 more source

Design Principles for Interactive Dashboards in Drug Safety Surveillance: Design Science Research.

JMIR Med Inform
Kotowicz M, Ferati M, Chowdhury S, Martins Pires C.   +3 more
europepmc   +1 more source

Horizon Scanning Methods for Health Care Technology Innovation Identification: Rapid Scoping Review of Patent Research Studies.

Interact J Med Res
Garcia Gonzalez-Moral S, Pennock E, Ewedairo O, Green E, Elgey J, Mkwashi A.   +5 more
europepmc   +1 more source

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User-centered Interactive Data Mining

2006 5th IEEE International Conference on Cognitive Informatics, 2006
While many data mining models concentrate on automation and efficiency, interactive data mining models focus on adaptive and effective communications between human users and computer systems. User requirements and preferences play the most important roles in human-machine interactions, and guide the selection of target knowledge representations ...
Yan Zho, Yaohua Chen, Yiyu Yao
openaire   +1 more source

Ubiquitous Mining with Interactive Data Mining Agents

Journal of Computer Science and Technology, 2009
Due to the increasing availability and sophistication of data recording techniques, multiple information sources and distributed computing are becoming the important trends of modern information systems. Many applications such as security informatics and social computing require a ubiquitous data analysis platform so that decisions can be made rapidly ...
Xin-Dong Wu, Xing-Quan Zhu, Qi-Jun Chen, Fei-Yue Wang   +3 more
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Mining Bursty Groups from Interaction Data

Proceedings of the 30th ACM International Conference on Information & Knowledge Management, 2021
Empirical studies and theoretical models both highlight burstinessas a common temporal pattern in online behavior. A key driver for burstiness is the self-exciting nature of online interactions. For example, posts in online groups often incite posts in response. Such temporal dependencies are easily lost when interaction data is aggregated in snapshots
Alexander Gorovits, Lin Zhang, Ekta Gujral, Evangelos Papalexakis, Petko Bogdanov   +4 more
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Interactive Visual Data Mining

2005
In the data mining field, people have no doubt that high level information (or knowledge) can be extracted from the database through the use of algorithms. However, a one-shot knowledge deduction is based on the assumption that the model developer knows the structure of knowledge to be deducted. This assumption may not be invalid in general.
Shouhong Wang, Hai Wang
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Data mining the protein data bank: Residue interactions

Proteins: Structure, Function, and Bioinformatics, 2002
AbstractThe protein databank contains a vast wealth of structural and functional information. The analysis of this macromolecular information has been the subject of considerable work in order to advance knowledge beyond the collection of molecular coordinates.
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Interactive pattern mining on hidden data

Proceedings of the 21st ACM international conference on Information and knowledge management, 2012
Mining frequent patterns from a hidden dataset is an important task with 43 various real-life applications. In this research, we propose a solution to this problem that is based on Markov Chain Monte Carlo (MCMC) sampling of frequent patterns. Instead of returning all the frequent patterns, the proposed paradigm returns a small set of randomly selected
Mansurul Bhuiyan, Snehasis Mukhopadhyay, Mohammad Al Hasan   +2 more
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