Collaborative Data Mining

Moyle, Steve

doi:10.1007/978-0-387-09823-4_54

Cited by 7 publications

(4 citation statements)

References 15 publications

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“…The experiments have been done for the following benchmarks: 1. oven 1, 13, respectively oven 14 alone; 2. oven 13 using the previous data for oven 14, respectively oven 14 using the previous data for oven 13. The two ovens have been chosen because there is a high correlation between them.…”

Section: Methodsmentioning

confidence: 99%

“…As stated in [13], collaborative data mining is a setting where the data mining effort and/or process is distributed among multiple collaborative agents that are autonomously executing actions in the environment. Collaborative data mining is based on the main assumption that collaborative data mining processes can better tackle the considered data mining process with respect to a data mining process built on the top of individual and non-collaborative agents.…”

Section: Collaborative Data Miningmentioning

confidence: 99%

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Collaborative Data Mining for Intelligent Home Appliances

Matei

Orio

Jassbi

et al. 2016

Collaboration in a Hyperconnected World

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The augmentation of physical devices and resources with electronics, software, sensing elements and network connectivity is a "hot topic" as confirmed also by the several research projects and activities on internet-of-things (IoT) and cyber-physical systems (CPS) research streams. It is obvious that intelligent products are taking more responsibility in future collaborative networks. Recent products are becoming more and more intelligent and connected by using the existing network infrastructure, meaning that products are becoming active agents in networks and valuable data sources that are capable to provide data continuously during their operation. This is leading to a massive amount of data that can be used by product manufacturers to be and remain competitive in market sharing. In this scenario, the application of collaborative data mining techniques, supported by machine learning algorithms, is aimed to enable the analysis of the data provided from multiple and above all distributed data sources in order to discover and extract useful knowledge about the behavior of the users along with the usage patterns of their devices and appliances.

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Section: Methodsmentioning

confidence: 99%

Section: Collaborative Data Miningmentioning

confidence: 99%

Collaborative Data Mining for Intelligent Home Appliances

Matei

Orio

Jassbi

et al. 2016

Collaboration in a Hyperconnected World

View full text Add to dashboard Cite

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“…As is mentioned in [15] by S. Moyle, data mining effort for collaborative data mining, it is larger and divided between all participants in the process.…”

Section: Research In Domainmentioning

confidence: 99%

“…The term of collaborative data mining has been used several times, by Appleman in [1], Maimon in [10] and Moyle in [15]. But the term is not defined in a comprehensive manner that allows one to have a view of what are the advantages of such an approach compared to classical data mining, what are the benefits of such an approach, what are the underlying principles of such an approach and how this approach may be different compared to other approaches.…”

Section: Collaborative Data Miningmentioning

confidence: 99%

Survey of Collaborative Data Mining

Anton

Matei

Avram

2019

Carpathian Journal of Electronic and Computer Engineering

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In the information industry there is a huge amount of data which can be used to obtain relevant information necessary for them to be processed, cleaned and analyzed. This survey paper presents different data extraction research that can be applied in various areas. The main point is to determine a new approach and to be the starting point for new experiments in agriculture predictions. The collaborative data mining approach assumes that correlated units or devices will have similar behavior that can be determined with an acceptable approximation.

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Applications of IVIFSs

Atanassov

2019

Interval-Valued Intuitionistic Fuzzy Sets

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Collaborative Data Mining

Cited by 7 publications

References 15 publications

Collaborative Data Mining for Intelligent Home Appliances

Collaborative Data Mining for Intelligent Home Appliances

Survey of Collaborative Data Mining

Applications of IVIFSs

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