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All Outputs (4)

Attention is Everything You Need: Case on Face Mask Classification (2023)
Journal Article
Pratama, N., Harianto, D., Filbert, S., Warnars, H. L. H. S., & Muyeba, M. K. (2023). Attention is Everything You Need: Case on Face Mask Classification. Procedia Computer Science, 227, 372-380. https://doi.org/10.1016/j.procs.2023.10.536

Automated face mask classification has surfaced recently following the COVID-19 mask wearing regulations. The current State-of-The-Art of this problem uses CNN-based methods such as ResNet. However, attention-based models such as Transformers emerged... Read More about Attention is Everything You Need: Case on Face Mask Classification.

A hybrid heuristic approach for attribute-oriented mining (2013)
Journal Article
Muyeba, M. K., Crockett, K., Wang, W., & Keane, J. A. (2014). A hybrid heuristic approach for attribute-oriented mining. Decision Support Systems, 57, 139-149. https://doi.org/10.1016/j.dss.2013.08.012

We present a hybrid heuristic algorithm, clusterAOI, that generates a more interesting generalised table than obtained via attribute-oriented induction (AOI). AOI tends to overgeneralise as it uses a fixed global static threshold to cluster and gener... Read More about A hybrid heuristic approach for attribute-oriented mining.

Business information query expansion through semantic network (2010)
Journal Article
Gong, Z., Muyeba, M., & Guo, J. (2010). Business information query expansion through semantic network. Enterprise Information Systems, 4(1), 1-22. https://doi.org/10.1080/17517570903502856

In this article, we propose a method for business information query expansions. In our approach, hypernym/hyponymy and synonym relations in WordNet are used as the basic expansion rules. Then we use WordNet Lexical Chains and WordNet semantic similar... Read More about Business information query expansion through semantic network.

Fuzzy Weighted Association Rule Mining with Weighted Support and Confidence Framework (2009)
Conference Proceeding
Muyeba, M., Khan, M. S., & Coenen, F. (2009). Fuzzy Weighted Association Rule Mining with Weighted Support and Confidence Framework. In New Frontiers in Applied Data Mining (49-61). https://doi.org/10.1007/978-3-642-00399-8_5

In this paper we extend the problem of mining weighted association rules. A classical model of boolean and fuzzy quantitative association rule mining is adopted to address the issue of invalidation of downward closure property (DCP) in weighted assoc... Read More about Fuzzy Weighted Association Rule Mining with Weighted Support and Confidence Framework.