Multi label text classification for un-trained data through supervised learning

Multi label text classification for un-trained data through supervised learning

World of digital data is growing at an aggressive rate, where every single minute new data is created and processed. All information retrieval processes are gone from insufficient to overflowing. It is doubling each and every year which makes information retrieval more challenging. Our focus is to t...

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Bibliographic Details
Main Author: BUDHIRAJA, Mayank
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2017
Subjects:
Multi label classification
supervised learning
un-trained data
lexion
MITB student
Databases and Information Systems
Data Science
Numerical Analysis and Scientific Computing
Online Access:https://ink.library.smu.edu.sg/sis_research/5991
https://doi.org/10.1109/I2C2.2017.8321804
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Institution: Singapore Management University
Language: English
Description
Summary:World of digital data is growing at an aggressive rate, where every single minute new data is created and processed. All information retrieval processes are gone from insufficient to overflowing. It is doubling each and every year which makes information retrieval more challenging. Our focus is to turn this immense data streams from a liability to our strengths.

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