Access the full text.
Sign up today, get DeepDyve free for 14 days.
V Bijalwan, V Kumar, P Kumari, J Pascual (2014)
KNN based machine learning approach for text and document miningInt J Database Theory Appl, 7
O-W Kwon, J-H Lee (2003)
Text categorization based on k-nearest neighbor approach for web site classificationInf Process Manag, 39
F Debole, F Sebastiani (2004)
Supervised term weighting for automated text categorization. Text mining and its applications
S Jiang, G Pang, M Wu, L Kuang (2012)
An improved K-nearest-neighbor algorithm for text categorizationExpert Syst Appl, 39
S Lai, L Xu, K Liu, J Zhao (2015)
Recurrent convolutional neural networks for text classificationAAAI, 333
AKS Tilve, SN Jain (2017)
A survey on machine learning techniques for text classificationInt J Eng Sci Res Technol, 6
VH Masand, DT Mahajan, KN Patil, KD Chinchkhede, RD Jawarkar, TB Hadda, AA Alafeefy, IG Shibi (2012)
k-NN, quantum mechanical and field similarity based analysis of xanthone derivatives as α-glucosidase inhibitorsMed Chem Res, 21
F Sebastiani (2006)
Classification of text, automaticEncycl Lang Linguist, 14
M Sahami, S Dumais, D Heckerman, E Horvitz (1998)
A Bayesian approach to filtering junk e-mailLearn Text Categ, 62
F Joseph, N Ramakrishnan (2015)
Text categorization using improved K nearest neighbor algorithmInt J Trends Eng Technol, 4
A Moreno, T Redondo (2016)
Text analytics: the convergence of big data and artificial intelligenceIJIMAI, 3
V Sharmila, I Vasudevan, GT Arasu (2014)
Pattern based classification for text mining using fuzzy similarity algorithmJ Theor Appl Inf Technol, 63
E Fix, JL Hodges (1951)
Discriminatory analysis-nonparametric discrimination: consistency properties
Ç Aytekin (2013)
An opinion mining task in Turkish language: a model for assigning opinions in Turkish blogs to the polaritiesJ Mass Commun, 3
J Hu, S Li, Y Yao, L Yu, G Yang, J Hu (2018)
Patent keyword extraction algorithm based on distributed representation for patent classificationEntropy, 20
S Vogrinčič, Z Bosnić (2011)
Ontology-based multi-label classification of economic articlesComput Sci Inf Syst, 8
CS Jothi, D Thenmozhi (2015)
Machine learning approach to document classification using concept based featuresInt J Comput Appl, 118
D Sharma (2012)
Stemming algorithms: a comparative study and their analysisInt J Appl Inf Syst, 4
N Suguna, K Thanushkodi (2010)
An improved K-nearest neighbor classification using Genetic AlgorithmInt J Comput Sci Issues, 7
M Ikonomakis, S Kotsiantis, V Tampakas (2005)
Text classification using machine learning techniquesWSEAS Trans Comput, 4
Q Kuang, X Xiaoming (2011)
An improved feature weighting method for text classificationAdv Inf Sci Service Sci, 3
J Han, J Pei, M Kamber (2011)
Data mining: concepts and techniques
EHS Han, G Karypis, V Kumar (2001)
Text categorization using weight adjusted k-nearest neighbor classification
V Vapnik (2000)
The nature of statistical learning theory
Y Saeys, I Inza, P Larrañaga (2007)
A review of feature selection techniques in bioinformaticsBioinformatics, 23
Y Feng, W Zhaohui, Z Zhou (2005)
Multi-label text categorization using k-nearest neighbor approach with m-similarity. String Processing and Information Retrieval
A Lausch, A Schmidt, L Tischendorf (2015)
Data mining and linked open data—new perspectives for data analysis in environmental researchEcol Model, 295
B Trstenjak, S Mikac, D Donko (2014)
KNN with TF-IDF based framework for text categorizationProc Eng, 69
S Xu (2018)
Bayesian Naïve Bayes classifiers to text classificationJ Inf Sci, 44
X Qi, BD Davison (2009)
Web page classification: features and algorithmsACM Comput Surv (CSUR), 41
M Sugiyama, M Kawanabe (2012)
Machine learning in non-stationary environments: introduction to covariate shift adaptation
Y Matsuo, M Ishizuka (2004)
Keyword extraction from a single document using word co-occurrence statistical informationInt J Artif Intell Tools, 13
A Mudgal, R Munjal (2015)
Role of support vector machine, fuzzy K-means and Naive Bayes classification in intrusion detection systemInt J Recent and Innov Trends Comput Commun, 3
Supervised machine learning studies are gaining more significant recently because of the availability of the increasing number of the electronic documents from different resources. Text classification can be defined that the task was automatically categorized a group documents into one or more predefined classes according to their subjects. Thereby, the major objective of text classification is to enable users for extracting information from textual resource and deals with process such as retrieval, classification, and machine learning techniques together in order to classify different pattern. In text classification technique, term weighting methods design suitable weights to the specific terms to enhance the text classification performance. This paper surveys of text classification, process of different term weighing methods and comparison between different classification techniques.
Artificial Intelligence Review – Springer Journals
Published: Jan 19, 2019
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.