K-SVMeans: A Hybrid Clustering Algorithm for Multi-Type Interrelated Datasets

Wang, Hai H.; Saleh, Ahmed I.; Payne, Terry R.; Gibbins, Nick

doi:10.1109/wi.2007.61

Cited by 10 publications

(6 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…. , N and yi 2 (À1, þ1), where N is the number of training samples, yi ¼ þ1 for class o1, and yi ¼ À1 for class o2 in case of which we have two classes and linearly separable, as expressed in the following equation (4) 8,13 :…”

Section: CImentioning

confidence: 99%

“…[1][2][3][4] Furthermore, the extraction and observation of the water body from the remote sensing data lead to easily and correctly determine various water resources monitoring, management, wetland classification, water/land cover segmentation, and coastline of lake detection. [5][6][7][8] This work aims to determine the Mosul Dam reservoir water case and monitor the quality of water and its impact on human health due to environmental and climatic changes that had occurred in recent years, which caused decline of water quantity and increase in pollution and sedimentation, which has been tested over a 31-year period. Thus, using temporal remote sensing data is the best choice for this work to observe the changing over the mentioned period.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Knowledge technologies based on fabrication process composite materials and remote sensing applications

Mustafa

Bayat

2020

Advanced Composites Letters

View full text Add to dashboard Cite

The aim of this work concentrates on utilizing powerful MATLAB programming (software version R2016a) to evaluate the impact of environmental variations of water case in the Mosul Dam reservoir and observed its receding impact on human life activities based on composite image processing applications. Furthermore, composite materials of different temporal remote sensing data increase powerfully the estimation of environmental variables of relevance to human health. Thus, temporal remote sensing data trends to enhance the efficiency of detecting receding water resources effect of human life impacts over different years. Two steps were implemented, which focuses on the estimation of changes in the water surface of the lake over 31 years. Preprocessing step concentrates on composite data materials from different Landsats to be more suitable for next step by utilizing color composite image processing and postprocessing step implemented the coastline detection of the reservoir and recognition of the quality of clear water in the lake due to the variation of water spectral reflectivity by hybrid classification method. The performance of this study is based on statistics measurements on the surface area of water level and overall accuracy, which indicated that hybrid classification method improves the capacity of integrating two classification methods, which gained highly identification water lake classes regarding its quality and more. The obtained results achieved the desired purpose of this study to investigate the high power application through implementing composite different image processing techniques with temporal satellite data to conversance the amount of water level changes in Mosul Dam reservoir and its impact on storage quantity over years.

show abstract

Section: CImentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Knowledge technologies based on fabrication process composite materials and remote sensing applications

Mustafa

Bayat

2020

Advanced Composites Letters

View full text Add to dashboard Cite

show abstract

“…Traditionally, clustering has been targeted to flat, single‐type datasets that can be represented as points in a multi‐dimensional vector space; new challenges are posed by the heterogeneous datasets, where relationships between objects are represented through multiple layers of connectivity and similarity (Bolelli et al , 2007). These challenges have been addressed by link‐based classification methods (Getoor and Diehl, 2005) and by multi‐type relational clustering (Li and Anand, 2008); in both contexts the definition of the similarity metrics (or distance) departures from the ones of classic clustering since it takes into account recursively the objects with which each object is related (linked).…”

Section: Educational Data Integration: Enrichment Clustering and Interlinking Educational Linked Datamentioning

confidence: 99%

“…These methods assume that the data comes from consistent tables and schemas; when these assumptions do not hold other methods may prove more effective. A recent approach to address heterogeneity of the data set is presented in (Bolelli et al , 2007), where each “block” of multi‐type information is seen as a source of similarity, these “blocks” taken together, can yield to better clustering results; the method used is K‐SVMeans, where K‐means is used together with support vector machines (SVM), a supervised classifier that helps preserving relation information when performing the clustering.…”

Section: Educational Data Integration: Enrichment Clustering and Interlinking Educational Linked Datamentioning

confidence: 99%

“…In Dietze et al (2012) and Kaldoudi et al (2011) clustering is provided through a web service that is configurable to allow the selection of the clustering algorithm and the metadata fields to consider for features extraction. This method is similar to the multi‐type approach of (Bolelli et al , 2007), since conceptually the metadata are partitioned in blocks of information that can be selected to contribute to the clustering, and focus the perspective of the clustering (e.g. capturing resources similarities based on the suggested “educational use”, rather than on the “subject”).…”

Section: Educational Data Integration: Enrichment Clustering and Interlinking Educational Linked Datamentioning

confidence: 99%

See 1 more Smart Citation

Interlinking educational resources and the web of data

Dietze

Sánchez‐Alonso

Ebner

et al. 2013

Program

View full text Add to dashboard Cite

PurposeResearch in the area of technology‐enhanced learning (TEL) throughout the last decade has largely focused on sharing and reusing educational resources and data. This effort has led to a fragmented landscape of competing metadata schemas, or interface mechanisms. More recently, semantic technologies were taken into account to improve interoperability. The linked data approach has emerged as the de facto standard for sharing data on the web. To this end, it is obvious that the application of linked data principles offers a large potential to solve interoperability issues in the field of TEL. This paper aims to address this issue.Design/methodology/approachIn this paper, approaches are surveyed that are aimed towards a vision of linked education, i.e. education which exploits educational web data. It particularly considers the exploitation of the wealth of already existing TEL data on the web by allowing its exposure as linked data and by taking into account automated enrichment and interlinking techniques to provide rich and well‐interlinked data for the educational domain.FindingsSo far web‐scale integration of educational resources is not facilitated, mainly due to the lack of take‐up of shared principles, datasets and schemas. However, linked data principles increasingly are recognized by the TEL community. The paper provides a structured assessment and classification of existing challenges and approaches, serving as potential guideline for researchers and practitioners in the field.Originality/valueBeing one of the first comprehensive surveys on the topic of linked data for education, the paper has the potential to become a widely recognized reference publication in the area.

show abstract

Short text clustering by finding core terms

Quan

et al. 2010

Knowl Inf Syst

View full text Add to dashboard Cite

K-SVMeans: A Hybrid Clustering Algorithm for Multi-Type Interrelated Datasets

Abstract: Identification of distinct clusters of documents in text col

Cited by 10 publications

References 22 publications

Knowledge technologies based on fabrication process composite materials and remote sensing applications

Knowledge technologies based on fabrication process composite materials and remote sensing applications

Interlinking educational resources and the web of data

Short text clustering by finding core terms

Contact Info

Product

Resources

About