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COMPARATIVE STUDY ON TEXT DOCUMENT CLUSTERING ALGORITHMS BASED ON LATENT SEMANTIC INDEXING

R.Jensi
2018 Zenodo  
In this paper, a comparative analysis of text document clustering algorithms based on latent semantic indexing dimension reduction technique is done.  ...  Text document clustering is the fastest growing research area for grouping enormous text documents in such a way that documents within a cluster have high intra-similarity and low inter-similarity to other  ...  PDDP is a SVD-based partitioning technique [10] . Fuzzy c-means (FCM) is a method of clustering which allows one piece of data to belong to two or more clusters.  ... 
doi:10.5281/zenodo.2533025 fatcat:fcmup3k4lvhnfch2x3zlhxlci4

COMPACT: A Comparative Package for Clustering Assessment [chapter]

Roy Varshavsky, Michal Linial, David Horn
2005 Lecture Notes in Computer Science  
COMPACT first reduces the dataset's dimensionality using the Singular Value Decomposition (SVD) method, and only then employs various clustering techniques.  ...  Besides its simplicity, and its ability to perform well on highdimensional data, it provides visualization tools for evaluating the results.  ...  Availability: COMPACT is available at http://www.protonet.cs.huji.ac.il/compact and at http://adios.tau.ac.il/compact . A detailed description of the application can be found on these websites.  ... 
doi:10.1007/11576259_18 fatcat:ff6qxufxpjcxpjbcyfsinacvcq

Taming Wild High Dimensional Text Data with a Fuzzy Lash [article]

Amir Karami
2017 arXiv   pre-print
Although a wide range of methods based on the UFT strategy has been developed, the fuzzy approach has not been considered for DR based on this strategy.  ...  The quantitative evaluation shows that fuzzy clustering produces superior performance and features to Principal Components Analysis (PCA) and Singular Value Decomposition (SVD), two popular DR methods  ...  Bag-of-words (BOW) is a common method in text data representation. This technique represents documents based on the frequency of words with a matrix [4] .  ... 
arXiv:1712.05997v1 fatcat:52j53o62kjclde6stgctytykxy

Automatic online spike sorting with singular value decomposition and fuzzy C-mean clustering

Andriy Oliynyk, Claudio Bonifazzi, Fernando Montani, Luciano Fadiga
2012 BMC Neuroscience  
After being trained on a short testing data stream, the method can reliably perform supervised online classification and monitoring of single neuron activity.  ...  The method is based on a combination of Singular Value Decomposition for fast and highly accurate pre-processing of spike shapes, unsupervised Fuzzy C-mean, high-resolution alignment of extracted spike  ...  The authors thank Stefano Panzeri for his feedback on software development and manuscript writing.  ... 
doi:10.1186/1471-2202-13-96 pmid:22871125 pmcid:PMC3473300 fatcat:zcuuo7r4fngpnhr65kaw32nbxq

Application of Fuzzy Clustering for Text Data Dimensionality Reduction [article]

Amir Karami
2019 arXiv   pre-print
Although several UFT-based methods have been developed, fuzzy clustering has not been considered for dimensionality reduction.  ...  Performance of fuzzy clustering with and without using global term weighting methods is shown to exceed principal component analysis and singular value decomposition.  ...  Applying GTW methods has a 72% and 100% positive effect on the performance of PCA and SVD, respectively. The highest effect of GTW methods is on SVD, followed by FC-2.5 with 72% positive effect.  ... 
arXiv:1909.10881v1 fatcat:zw3ixh7drvfo7gl6bj3oab65ou

Document Clustering Using Concept Space and Cosine Similarity Measurement

Lailil Muflikhah, Baharum Baharudin
2009 2009 International Conference on Computer Technology and Development  
Document clustering is related to data clustering concept which is one of data mining tasks and unsupervised classification.  ...  It is often applied to the huge data in order to make a partition based on their similarity. Initially, it used for Information Retrieval in order to improve the precision and recall from query.  ...  FUZZY C-MEANS CLUSTERING There are various fuzzy clustering algorithms and one simple fuzzy clustering technique is the fuzzy c-means algorithm (FCM) by Duda and Hart [13] which was birth of fuzzy method  ... 
doi:10.1109/icctd.2009.206 fatcat:3puu2erdeba7fp6enelqv3b7de

Classification of Hydro Chemical Data in the Reduced Dimensional Space

Jasminka Dobša, Petr Praus, Aswani Kumar Cherukuri, Pavel Praks
2012 Journal of Information and Organizational Sciences  
and further on the space of centroids of classes.  ...  We compare the classification of full data representation to the classification of data items in lower dimensional space obtained by projection of original data on the space of first principal components  ...  Acknowledgements One of the authors, Ch.  ... 
doaj:46e96911abdc4783800a15a39346b05f fatcat:sw2nooszerbezl3qd3ifufq2cq

A hybrid group-based movie recommendation framework with overlapping memberships

Yasher Ali, Osman Khalid, Imran Ali Khan, Syed Sajid Hussain, Faisal Rehman, Sajid Siraj, Raheel Nawaz, Sriparna Saha
2022 PLoS ONE  
Unlike the existing group recommender systems that use traditional methods like K-Means, Pearson correlation, and cosine similarity to form groups, we use Fuzzy C-means clustering which assigns a degree  ...  The experiments were conducted on MovieLens 1M dataset where we used Neural Collaborative Filtering to recommend Top-k movies to each group.  ...  In Fig 5(a), the comparison is based on Precision, which is 0.8960, 0.9440, and 1.0 for ALS, SVD, and HTGF, respectively. The comparison based on recall is described in Fig 5(b).  ... 
doi:10.1371/journal.pone.0266103 pmid:35358269 pmcid:PMC8970527 fatcat:7ksdl3tomvg6bpdjvts2og5wva

A computational intelligence approach to efficiently predicting review ratings in e-commerce

Georgina Cosma, Giovanni Acampora
2016 Applied Soft Computing  
In particular, the proposed framework integrates the techniques of Singular Value Decomposition (SVD) and dimensionality reduction, Fuzzy C-Means (FCM) and the Adaptive Neuro-Fuzzy Inference System (ANFIS  ...  In addition, the proposed framework can be utilised for other classification and prediction tasks, and its neuro-fuzzy predictor module can be replaced by other classifiers.  ...  Prabowo and Thelwall [9] proposed a method combining the rule-based classification and supervised learning approaches.  ... 
doi:10.1016/j.asoc.2016.02.024 fatcat:2htf3ihtavhllomtluqopjf3kq

Fuzzy Approach Topic Discovery in Health and Medical Corpora

Amir Karami, Aryya Gangopadhyay, Bin Zhou, Hadi Kharrazi
2017 International Journal of Fuzzy Systems  
Powerful methods have been developed in recent years to make the text processing automatic.  ...  One of the popular approaches to retrieve information based on discovering the themes in health & medical corpora is topic modeling, however, this approach still needs new perspectives.  ...  One of the popular methods in medical text data representation is bag-of-words (BOW). This technique represents documents based on the frequency of words with a matrix like A.  ... 
doi:10.1007/s40815-017-0327-9 fatcat:yti2unl6m5gvpmg2v3siq7vlxe

EFFICIENT DATA MINING TECHNIQUES FOR BIG DATA ANALYSIS: A SURVEY

M. Amsaveni, PG and Research Department of Computer Science Chikkanna Govt Arts College Tirupur,Tamil Nadu, India.
2018 International Journal of Advanced Research in Computer Science  
At first, different dimensionality reduction, clustering and classification methods proposed for big data analysis in previous researches are studied in detail.  ...  In this article, a detailed comparative survey on different processes of big data mining techniques such as dimensionality reduction, clustering and classification for big data analysis is presented.  ...  The big data classification methods described in the above section is analyzed and compared based on methods used, their merits, demerits and the parameters used in experimental results.  ... 
doi:10.26483/ijarcs.v9i6.6348 fatcat:prkimvn4tnefjnw4ivthjiptq4

A fuzzy clustering method of construction of ontology-based user profiles

Lixin Han, Guihai Chen
2009 Advances in Engineering Software  
Another key feature of FCOU is that it employs the combination of FCM, PHR and simulated annealing to develop ontology-based user profiles.  ...  In this paper, we propose a fuzzy clustering method of construction of ontology-based user profiles (FCOU).  ...  The FCOU method employs the combination of FCM, PHR algorithm and simulated annealing to develop ontology-based user profiles.  ... 
doi:10.1016/j.advengsoft.2008.10.006 fatcat:opi2dfq7gfho7ckxfffyv4ldny

Advances in Meta-Heuristic Optimization Algorithms in Big Data Text Clustering

Laith Abualigah, Amir H. Gandomi, Mohamed Abd Elaziz, Husam Al Hamad, Mahmoud Omari, Mohammad Alshinwan, Ahmad M. Khasawneh
2021 Electronics  
This paper reviews all of the relevant literature on meta-heuristic-based text clustering applications, including many variants, such as basic, modified, hybridized, and multi-objective methods.  ...  This paper presents a comprehensive survey of the meta-heuristic optimization algorithms on the text clustering applications and highlights its main procedures.  ...  The performance of the results of the clustering depends significantly on the text classification and the clustering method.  ... 
doi:10.3390/electronics10020101 fatcat:fb3sopje4fegphs5b6g673ipqa

Image segmentation based on adaptive cluster prototype estimation

A.W.-C. Liew, Hong Yan, N.F. Law
2005 IEEE transactions on fuzzy systems  
An image segmentation algorithm based on adaptive fuzzy c-means (FCM) clustering is presented in this paper.  ...  Recently, she has also been working on Web-based system design and video searching for internet applications.  ...  segmentation compared to the conventional FCM and several FCM-based algorithms.  ... 
doi:10.1109/tfuzz.2004.841748 fatcat:b5hrryn545arvl23x7kvv7qxtu

Probabilistic Unsupervised Machine Learning Approach for a Similar Image Recommender System for E-Commerce

Ssvr Kumar Addagarla, Anthoniraj Amalanathan
2020 Symmetry  
Currently, many e-commerce platforms use a text-based product search, which has limitations to fetch the most similar products.  ...  We computed various cluster performance metrics on K-means++ and achieved a Silhouette Coefficient (SC) of 0.1414, a Calinski-Harabasz (CH) index score of 669.4, and a Davies–Bouldin (DB) index score of  ...  Karthikeyan and Aruna [24] proposed a probabilistic text and image-based semi-supervised clustering approach.  ... 
doi:10.3390/sym12111783 fatcat:4ean33e7effupof6bnjlj5grhe
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