Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Reducing approximation error with rapid convergence rate for non-negative matrix factorization (NMF) Subject The topic of the resource Clustering; Document Retrieval; Non-Negative Matrix Factorization (NMF); Singular Value Decomposition (SVD) Description An account of the resource Non-Negative Matrix Factorization (NMF) is utilized in many important applications. This paper presents development of an efficient low rank approximate NMF algorithm for feature extraction related to text mining and spectral data analysis. NMF can be used for clustering. NMF factorizes a positive matrix A to two positive matrices W and H matrices where A = WH. The proposal uses k-means clustering algorithm to determine the centroid of each cluster and assigns the centroid coordinates of each cluster as one column for W matrix. The initial choice of W matrix is positive. The H matrix is determined with gradient descent algorithm based on thin QR optimization. The performance comparison of the proposed NMF algorithm is illustrated with results. The accurate choice of initial positive W matrix reduces approximation error and the use of thin QR algorithm in combination with gradient descent approach provides rapid convergence rate for NMF. The proposed algorithm is implemented with the randomly generated matrix in MATLAB environment. The number of significant singular values of the generated matrix is selected as the number of clusters. The error and convergence rate comparison of the proposed algorithm with the current algorithms are demonstrated in this research. The accurate measurement of execution time for individual program is not possible in MATLAB. The average time execution over 200 iterations is therefore calculated with an increasing iteration count of the proposed algorithm and the comparative results are presented. 2021 by authors, all rights reserved. Creator An entity primarily responsible for making the resource Biswas J.; Kayal P.; Samanta D. Source A related resource from which the described resource is derived Mathematics and Statistics, Vol-9, No. 3, pp. 285-289. Publisher An entity responsible for making the resource available Horizon Research Publishing Date A point or period of time associated with an event in the lifecycle of the resource 2021-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.13189/ms.2021.090309" target="_blank" rel="noreferrer noopener">https://doi.org/10.13189/ms.2021.090309</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85105660636&amp;doi=10.13189%2Fms.2021.090309&amp;partnerID=40&amp;md5=c9a363a5ab129aff482b82d71e75c847" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85105660636&amp;doi=10.13189%2fms.2021.090309&amp;partnerID=40&amp;md5=c9a363a5ab129aff482b82d71e75c847</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access Relation A related resource ISSN: 23322071 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Biswas J., Department of Computer Science, Christ University, Bangalore, India; Kayal P., Don Bosco School, Park Circus, Kolkata, India; Samanta D., Department of Computer Science, Christ University, Bangalore, India