Heterogenetic knowledge classification Using Fuzzy inference for unified data clusters

Farooq, Umer and Ahmad, Khalil (2020) Heterogenetic knowledge classification Using Fuzzy inference for unified data clusters. EAI Endorsed Transactions on Scalable Information Systems, 7 (24): e3. ISSN 2032-9407

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Abstract

Emerging technologies such as Cloud Computing, Internet of Things (IoT) and Big Data are developing a digital ecosystem. This ecosystem is catering diverse types and volumes of data that represents information segments. The essence of these segments become vital when transformed into knowledge units to provide a more meaningful and productive perspective. The transformed knowledge at this stage is heterogenetic in nature, consisting of functional and structural properties which needs to be arranged to formulate robust and efficient knowledge repositories. The heterogenetic knowledge can be transformed into classification clusters using structural properties by controlling the degree of heterogeneity. In this paper, Fuzzy Inference System (FIS) based classification approach is proposed for heterogenetic knowledge clustering.

Item Type: Article
Uncontrolled Keywords: GPS, IoT, FIS, Knowledge Heterogeneity, Knowledge System
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
QA75 Electronic computers. Computer science
Depositing User: EAI Editor II.
Date Deposited: 08 Oct 2020 13:53
Last Modified: 08 Oct 2020 13:53
URI: https://eprints.eudl.eu/id/eprint/683

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