Recommendation Algorithm Combining Tag Data and Naive Bayes Classification

He, Deniu; He, Zhanjun; Liu, C

doi:10.1109/icedme50972.2020.00156

Cited by 5 publications

(2 citation statements)

References 12 publications

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“…This procedure has also been mentioned as a method to prognosis in industrial cases [2]. Label data can also utilize naïve Bayes classification to infer the category of the new data [25]. In this research, naïve Bayes classification is combined with hierarchical clustering.…”

Section: Naïve Bayes Classificationmentioning

confidence: 99%

Comparison of structural analysis and principle component analysis for leakage prediction on superheater in boiler

Budi

Ekawati

Efendy

2022

IJ-AI

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<span>Leakage is one of the failures which commonly happens in boiler operation. Moreover, a continuous unsettled anomaly in a boiler could lead to leakage failure. An algorithm has been developed to predict the failure, consisting of three general procedures: feature selection, followed by hierarchical clustering, and naïve Bayes classification. The hierarchical clustering changes unlabeled data into labeled data, and naïve Bayes classification calculates the probability to justify anomaly occurrence. Meanwhile, this research focused on the effect of the feature selection method on the result of leakage prediction. Two different feature selection methods, namely the structural analysis and the principal component analysis (PCA), were deployed separately and then compared. The result showed that leakage prediction using the structural analysis method gave 13 hours 40 minutes of prediction time, and the PCA method gave 25 hours of prediction time. However, the PCA feature selection method caused more false alarms than feature selection with structural analysis, which only triggered five false alarms a week before leakage. Moreover, the structural analysis offered better traceability than PCA to understand the leakage occurrence.</span>

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Section: Naïve Bayes Classificationmentioning

confidence: 99%

Comparison of structural analysis and principle component analysis for leakage prediction on superheater in boiler

Budi

Ekawati

Efendy

2022

IJ-AI

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“…Tag extension is the process of finding similar tags for each tag or calculating tag similarity. To quantify the similarity between tags using cosine similarity [18].…”

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confidence: 99%

An enhanced framework for solving cold start problem in movie recommendation systems

Elzeheiry

Mekky²,

Atwan³

et al. 2021

IJEECS

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<p>Recommendation systems (RSs) are used to obtain advice regarding decision-making. RSs have the shortcoming that a system cannot draw inferences for users or items regarding which it has not yet gathered sufficient information. This issue is known as the cold start issue. Aiming to alleviate the user’s cold start issue, the proposed recommendation algorithm combined tag data and logistic regression classification to predict the probability of the movies for a new user. First using alternating least square to extract product feature, and then diminish the feature vector by combining principal component analysis with logistic regression to predict the probability of genres of the movies. Finally, combining the most relevant tags based on similarity score with probability and find top N movies with high scores to the user. The proposed model is assessed using the root mean square error (RMSE), the mean absolute error (MAE), recall@N and precision@N and it is applied to 1M, 10M and 20M MovieLens datasets, resulting in an accuracy of 0.8806, 0.8791 and 0.8739.</p>

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Breast Cancer Prediction of Benign and Malignant Tumors by Classification Algorithms

Promtan,

Khongthong,

Choksuchat

2023

2023 4th International Conference on Big Data Analytics and Practices (IBDAP)

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Recommendation Algorithm Combining Tag Data and Naive Bayes Classification

Cited by 5 publications

References 12 publications

Comparison of structural analysis and principle component analysis for leakage prediction on superheater in boiler

Comparison of structural analysis and principle component analysis for leakage prediction on superheater in boiler

An enhanced framework for solving cold start problem in movie recommendation systems

Breast Cancer Prediction of Benign and Malignant Tumors by Classification Algorithms

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