Improved class definition in two dimensional linear discriminant analysis of speech

Conka, David; Viszlay, Peter; Juhar, Jozef

doi:10.1109/radioelek.2015.7129025

Cited by 3 publications

(2 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…With that, experts suggested or established means to automatically create the class labels for LDA such as PCA-LDA which used Principal Component Analysis (PCA) to separate the classes [46], and ULDA which used target generation process (TGP) for the targets and classes [47]. LDA-Km [48], TRACK [49], Semi-LDC [10], and modified-2DLDA [50] utilized k-means clustering to make the class labels. Further, LDA-basis sequence calculates the projected class numbers and produces a sequence of bases that meets to the practical LDA solutions [8].…”

Section: Literature Reviewmentioning

confidence: 99%

Bandwidth Allocation Mechanism based on Users' Web Usage Patterns for Campus Networks

Paredes¹,

Sison²,

Medina³

2022

Int. j. commun. netw. inf. secur.

View full text Add to dashboard Cite

Managing the bandwidth in campus networks becomes a challenge in recent years. The limited bandwidth resource and continuous growth of users make the IT managers think on the strategies concerning bandwidth allocation. This paper introduces a mechanism for allocating bandwidth based on the users’ web usage patterns. The main purpose is to set a higher bandwidth to the users who are inclined to browsing educational websites compared to those who are not. In attaining this proposed technique, some stages need to be done. These are the preprocessing of the weblogs, class labeling of the dataset, computation of the feature subspaces, training for the development of the ANN for LDA/GSVD algorithm, visualization, and bandwidth allocation. The proposed method was applied to real weblogs from university’s proxy servers. The results indicate that the proposed method is useful in classifying those users who used the internet in an educational way and those who are not. Thus, the developed ANN for LDA/GSVD algorithm outperformed the existing algorithm up to 50% which indicates that this approach is efficient. Further, based on the results, few users browsed educational contents. Through this mechanism, users will be encouraged to use the internet for educational purposes. Moreover, IT managers can make better plans to optimize the distribution of bandwidth.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Bandwidth Allocation Mechanism based on Users' Web Usage Patterns for Campus Networks

Paredes¹,

Sison²,

Medina³

2022

Int. j. commun. netw. inf. secur.

View full text Add to dashboard Cite

show abstract

“…There were several ways to manage the unlabeled dataset most common method approach is making LDA unsupervised by utilizing clustering algorithms [9,[14][15][16]. With that, SelfOrganizing Map (SOM) was employed in creating the clusters or making of the class labels because it is an unsupervised learning technique to discover patterns to the dataset and it can deal with high dimensional data [17].…”

mentioning

confidence: 99%

Allocating Bandwidth Based on Users’ Web Usage Patterns for University Networks: A Hybrid Data Mining Approach

2018

LBGIS-18,ICASET-18,ECBMS-2018,LEHSS-18 June 14-15, 2018 Cebu (Philippines)

View full text Add to dashboard Cite

Abstract-Due to the limited bandwidth and continuous growth of users make the IT managers focus on the strategies concerning bandwidth allocation. Thus, managing the bandwidth in campus networks has become one of the challenges in recent years. This paper introduces a mechanism for bandwidth allocation based on the users' web usage patterns. The main purpose is to set a higher bandwidth to the users who are inclined to browsing educational websites compared to those who are not. In attaining this proposed technique, a hybrid data mining approach were done which composed of preprocessing of the weblogs, class labeling of the dataset, computation of the feature subspaces, training for the development of the ANN for LDA/GSVD algorithm, and visualization. The proposed method was applied to real weblogs from university's proxy servers which include 104 active users. The results indicate that the proposed method is useful in classifying those users who used the internet in an educational way and those who are not. Thus, the developed ANN for LDA/GSVD algorithm outperformed the existing algorithm up to 50% which indicates that this approach is efficient. Based on the results, 35.06% of the users browsed educational contents. Through this technique, users will be encouraged by using the internet for educational purposes. Moreover, IT managers can make better decisions to optimize the allocation of bandwidth resources.

show abstract

Fuzzy clustering in HMM-based triphone classes of 2DLDA in Slovak LVCSR

Conka

Viszlay

Juhar

2016

2016 International Conference on Systems, Signals and Image Processing (IWSSIP)

View full text Add to dashboard Cite

Improved class definition in two dimensional linear discriminant analysis of speech

Cited by 3 publications

References 7 publications

Bandwidth Allocation Mechanism based on Users' Web Usage Patterns for Campus Networks

Bandwidth Allocation Mechanism based on Users' Web Usage Patterns for Campus Networks

Allocating Bandwidth Based on Users’ Web Usage Patterns for University Networks: A Hybrid Data Mining Approach

Fuzzy clustering in HMM-based triphone classes of 2DLDA in Slovak LVCSR

Contact Info

Product

Resources

About