چکیده مقاله
The growing rise of databases almost in every area of human activity has caused the need for new powerful tools to change the suitable knowledge increase In order to satisfy this need, the researches of various fields such as machine learning, pattern identification, analysis of statistical data, data visualization, neural networks, econometrics, information retrieving, information extraction, etc have explored some methods and ideas Text mining uses unstructured textual information, studying it in order to discover the structure and hidden lateral meanings in the text Documents’ clustering via unsupervised machine learning methods has an expanded function in different areas of natural processing languages such as automatic multi text summarization, information retrieving, etc The current paper aims to introduce some useful functions of this area, clustering the documents with the approach of decreasing noise redundancy as well as unrelated data Dimension reduction is a method of erasing such features
کلیدواژهها
نویسندگان
Mohsen Hajighorbani
Young Researchers and Elite Club Islamic Azad University Qazvin, Iran
B.Minaei Bidgoli
Department of Computer Engineering, Iran University of Science and Technology, Tehran, Iran
Seyyed Mohammad Reza Hashemi
Young Researchers and Elite Club Islamic Azad University Qazvin, Iran
Mohammad Mahdi Deramgozin
Young Researchers and Elite Club Islamic Azad University Qazvin, Iran
شیوه ارجاع
Hajighorbani, Mohsen and Bidgoli, B.Minaei and Hashemi, Seyyed Mohammad Reza and Deramgozin, Mohammad Mahdi,1395,Survey of Document’s Clustering Methods by Means of Learning Algorithms,2nd National Congress of Electrical and Computer Engineering of Iran,Ramsar
ارائهشده در
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