Survey on supervised machine learning techniques for automatic text classification
AI Kadhim - Artificial intelligence review, 2019 - Springer
Supervised machine learning studies are gaining more significant recently because of the
availability of the increasing number of the electronic documents from different resources …
availability of the increasing number of the electronic documents from different resources …
[HTML][HTML] A review of machine learning algorithms for identification and classification of non-functional requirements
M Binkhonain, L Zhao - Expert Systems with Applications: X, 2019 - Elsevier
Context Recent developments in requirements engineering (RE) methods have seen a
surge in using machine-learning (ML) algorithms to solve some difficult RE problems. One …
surge in using machine-learning (ML) algorithms to solve some difficult RE problems. One …
[HTML][HTML] Analytics of machine learning-based algorithms for text classification
Text classification is the most vital area in natural language processing in which text data is
automatically sorted into a predefined set of classes. The application of text classification is …
automatically sorted into a predefined set of classes. The application of text classification is …
A novel multivariate filter method for feature selection in text classification problems
With increasing number of documents in digital format, automatic text categorization has
become a crucial task in pattern recognition problems. To ease the classification task …
become a crucial task in pattern recognition problems. To ease the classification task …
Performance analysis of different types of machine learning classifiers for non-technical loss detection
With the ever-growing demand of electric power, it is quite challenging to detect and prevent
Non-Technical Loss (NTL) in power industries. NTL is committed by meter bypassing …
Non-Technical Loss (NTL) in power industries. NTL is committed by meter bypassing …
On the feature selection and classification based on information gain for document sentiment analysis
AI Pratiwi, Adiwijaya - Applied Computational Intelligence and …, 2018 - Wiley Online Library
Sentiment analysis in a movie review is the needs of today lifestyle. Unfortunately, enormous
features make the sentiment of analysis slow and less sensitive. Finding the optimum feature …
features make the sentiment of analysis slow and less sensitive. Finding the optimum feature …
Machine learning approach for sentiment analysis
Abstract Machine learning algorithms have been widely used for sentiment analysis [66].
The bag-of-words (BoW) representation is commonly used for sentiment analysis [63, 93] …
The bag-of-words (BoW) representation is commonly used for sentiment analysis [63, 93] …
[图书][B] Prominent feature extraction for sentiment analysis
The field of sentiment analysis is an exciting and new research direction due to a large
number of real-world applications. Discovering people's opinion is very important for better …
number of real-world applications. Discovering people's opinion is very important for better …
Emotion detection in roman urdu text using machine learning
Emotion detection is playing a very important role in our life. People express their emotions
in different ways ie face expression, gestures, speech, and text. This research focuses on …
in different ways ie face expression, gestures, speech, and text. This research focuses on …
A multi-objective genetic algorithm for text feature selection using the relative discriminative criterion
With exponentially increasing the number of digital documents, text classification has
become a major task in data science applications. Selecting discriminative features highly …
become a major task in data science applications. Selecting discriminative features highly …