Challenges and issues in sentiment analysis: A comprehensive survey
Sentiment analysis, a specialization of natural language processing (NLP), has witnessed
significant progress since its emergence in the late 1990s, owing to the swift advances in …
significant progress since its emergence in the late 1990s, owing to the swift advances in …
An enhanced hybrid feature selection technique using term frequency-inverse document frequency and support vector machine-recursive feature elimination for …
Sentiment classification is increasingly used to automatically identify a positive or negative
sentiment in a text review. In classification, feature selection had always been a critical and …
sentiment in a text review. In classification, feature selection had always been a critical and …
A review study on arabic text classification
Documents contain a vast amount of crucial human information. The substantial rise in the
number of electronic documents available for personal or public usage necessitates the …
number of electronic documents available for personal or public usage necessitates the …
A visual analysis approach for data transformation via domain knowledge and intelligent models
Industry benchmarking involves comparing and analyzing a company's performance with
other top-performing enterprises. PDF documents contain valuable corporate information …
other top-performing enterprises. PDF documents contain valuable corporate information …
[PDF][PDF] Converting text to numerical representation using modified Bayesian vectorization technique for multi-class classification
The first step towards making the text documents machine-readable is vectorization.
Vectorisation allows the machines to understand textual content by transforming it into …
Vectorisation allows the machines to understand textual content by transforming it into …
A BERT-based Text Sentiment Classification Algorithm through Web Data
G Li, B Kong, J Li, H Fan, J Zhang, Y An… - 2022 International …, 2022 - ieeexplore.ieee.org
In order to analyze the sentiment tendency of public opinion, this paper conducts a textual
sentiment classification research through web data. In the research, this paper uses the …
sentiment classification research through web data. In the research, this paper uses the …
SNAD arabic dataset for deep learning
D AlSaleh, MB AlAmir… - Intelligent Systems and …, 2021 - Springer
Natural language processing (NLP) captured the attention of researchers for the last years.
NLP is applied in various applications and several disciplines. Arabic is a language that also …
NLP is applied in various applications and several disciplines. Arabic is a language that also …
[PDF][PDF] Hybridized Dimensionality Reduction Method for Machine Learning based Web Pages Classification
TS Sabbah - Iraqi Journal of Computers, Communications, Control …, 2022 - iasj.net
Feature space high dimensionality is a well-known problem in text classification and web
mining domains, it is caused mainly by the large number of vocabularies contained within …
mining domains, it is caused mainly by the large number of vocabularies contained within …
[PDF][PDF] Dimensionality Reduction for Classification of Filipino Text Documents based on Improved Bayesian Vectorization
Dimensionality reduction of feature vector size plays a vital role in enhancing the text
processing capabilities to reduce the size of the feature vector used in the mining tasks to …
processing capabilities to reduce the size of the feature vector used in the mining tasks to …
Measuring the Impact of Using Different Tools on Classification System Results
ZA Khalaf, ZM Jawad - Journal of Physics: Conference Series, 2020 - iopscience.iop.org
A huge amount of textual data is available on the web. These data need to be classified
under labels or classes to make the search more efficient and easier. Achieved by using …
under labels or classes to make the search more efficient and easier. Achieved by using …