Text classification techniques: A literature review
M Thangaraj, M Sivakami - Interdisciplinary journal of …, 2018 - search.proquest.com
Text Classification Techniques: A Literature Review Page 1 Volume 13, 2018 Accepted by
Editor Maureen Tanner│ Received: July 7 3, 2017│ Revised: October 31, 2017, January …
Editor Maureen Tanner│ Received: July 7 3, 2017│ Revised: October 31, 2017, January …
Feature weighting methods: A review
In the last decades, a wide portfolio of Feature Weighting (FW) methods have been
proposed in the literature. Their main potential is the capability to transform the features in …
proposed in the literature. Their main potential is the capability to transform the features in …
[HTML][HTML] Big Data sources and methods for social and economic analyses
D Blazquez, J Domenech - Technological Forecasting and Social Change, 2018 - Elsevier
Abstract The Data Big Bang that the development of the ICTs has raised is providing us with
a stream of fresh and digitized data related to how people, companies and other …
a stream of fresh and digitized data related to how people, companies and other …
Feature weighting and SVM parameters optimization based on genetic algorithms for classification problems
Abstract Support Vector Machines (SVMs) are widely known as an efficient supervised
learning model for classification problems. However, the success of an SVM classifier …
learning model for classification problems. However, the success of an SVM classifier …
[HTML][HTML] Detecting flooding DDoS attacks in software defined networks using supervised learning techniques
For the easy and flexible management of large scale networks, Software-Defined
Networking (SDN) is a strong candidate technology that offers centralisation and …
Networking (SDN) is a strong candidate technology that offers centralisation and …
[PDF][PDF] A novel classification approach based on Naïve Bayes for Twitter sentiment analysis
J Song, KT Kim, B Lee, S Kim… - KSII Transactions on …, 2017 - koreascience.kr
With rapid growth of web technology and dissemination of smart devices, social networking
service (SNS) is widely used. As a result, huge amount of data are generated from SNS such …
service (SNS) is widely used. As a result, huge amount of data are generated from SNS such …
A feature selection method based on hybrid improved binary quantum particle swarm optimization
Q Wu, Z Ma, J Fan, G Xu, Y Shen - IEEE access, 2019 - ieeexplore.ieee.org
As the volume of data available for analysis grows, feature selection is becoming a vital part
of ensuring accurate classification results. In classification problems, selecting a small …
of ensuring accurate classification results. In classification problems, selecting a small …
Rule-based back propagation neural networks for various precision rough set presented KANSEI knowledge prediction: a case study on shoe product form features …
Nonlinear operators for KANSEI evaluation dataset were significantly developed such as
uncertainty reason techniques including rough set, fuzzy set and neural networks. In order to …
uncertainty reason techniques including rough set, fuzzy set and neural networks. In order to …
Memetic extreme learning machine
Abstract Extreme Learning Machine (ELM) is a promising model for training single-hidden
layer feedforward networks (SLFNs) and has been widely used for classification. However …
layer feedforward networks (SLFNs) and has been widely used for classification. However …
A greedy belief rule base generation and learning method for classification problem
Among many rule-based systems employed in classification problems, the belief rule-based
(BRB) system has been significant for its ability to deal with both quantitative and qualitative …
(BRB) system has been significant for its ability to deal with both quantitative and qualitative …