Fuzzy clustering-based semi-supervised approach for outlier detection in big text data

Lazhar, Farek

doi:10.1007/s13748-018-0165-5

Cited by 6 publications

(2 citation statements)

References 20 publications

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“…In addition, the two-stage fuzzy approach can be applied to a situation where the number of released wafers to fabricate a specific product types fluctuates. Further, other data-preprocessing mechanisms can be used, such as input-data analysis mechanisms [71] or outlier-filtering mechanisms [72], to improve the credibility of the input data, thereby enhancing the reliability of the two-stage fuzzy approach.…”

Section: Discussionmentioning

confidence: 99%

Energy-Efficient Production Planning Using a Two-Stage Fuzzy Approach

Tsai

Chen

et al. 2021

Mathematics

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Analyzing energy consumption is an important task for a factory. In order to accomplish this task, most studies fit the relationship between energy consumption and product design features, process characteristics, or equipment types. However, the energy-saving effects of product yield learning are rarely considered. To bridge this gap, this study proposes a two-stage fuzzy approach to estimate the energy savings brought about by yield improvement. In the two-stage fuzzy approach, a fuzzy polynomial programming approach is first utilized to fit the yield-learning process of a product. Then, the relationship between monthly electricity consumption and increase in yield was fit to estimate the energy savings brought about by the improvement in yield. The actual case of a dynamic random-access memory factory was used to illustrate the applicability of the two-stage fuzzy approach. According to the experiment results, product yield learning can greatly reduce electricity consumption.

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Section: Discussionmentioning

confidence: 99%

Energy-Efficient Production Planning Using a Two-Stage Fuzzy Approach

Tsai

Chen

et al. 2021

Mathematics

View full text Add to dashboard Cite

show abstract

“…The results presented in Gôlo et al (2020) also demonstrate that tf-idf was the term-weighting scheme that provided the best classification results, and that the dimensionality reduction techniques do not necessarily have a positive impact on the classification performance. Manevitz and Yousef (2007) Lazhar (2019) used Fuzzy clustering to detect anomalous text documents. The method assumes that documents assigned to different groups with very close percentages are candidates for being outliers.…”

Section: One-class Learningmentioning

confidence: 99%