Systematic literature review of sentiment analysis on Twitter using soft computing techniques
Sentiment detection and classification is the latest fad for social analytics on Web. With the
array of practical applications in healthcare, finance, media, consumer markets, and …
array of practical applications in healthcare, finance, media, consumer markets, and …
[HTML][HTML] Big data-driven correlation analysis based on clustering for energy-intensive manufacturing industries
Abstract In Industry 4.0, the production data obtained from the Internet of Things has reached
the magnitude of big data with the emergence of advanced information and communication …
the magnitude of big data with the emergence of advanced information and communication …
Ensemble feature selection in medical datasets: Combining filter, wrapper, and embedded feature selection results
Feature selection is a process aimed at filtering out unrepresentative features from a given
dataset, usually allowing the later data mining and analysis steps to produce better results …
dataset, usually allowing the later data mining and analysis steps to produce better results …
Segmentation and classification of brain tumors using modified median noise filter and deep learning approaches
The most vital challenge for a radiologist is locating the brain tumors in the earlier stage. As
the brain tumor grows rapidly, doubling its actual size in about twenty-five days. If not dealt …
the brain tumor grows rapidly, doubling its actual size in about twenty-five days. If not dealt …
The optimal combination of feature selection and data discretization: An empirical study
CF Tsai, YC Chen - Information Sciences, 2019 - Elsevier
Feature selection and data discretization are two important data pre-processing steps in
data mining, with the focus in the former being on filtering out unrepresentative features and …
data mining, with the focus in the former being on filtering out unrepresentative features and …
Feature selection using hybrid poor and rich optimization algorithm for text classification
In order to reduce the high dimensional feature space in the text classification, feature
selection plays a significant role. The dimension reduction of feature space reduces the …
selection plays a significant role. The dimension reduction of feature space reduces the …
Assessing the reTweet proneness of tweets: predictive models for retweeting
The problem of assessing the mechanisms underlying the phenomenon of virality of social
network posts is of great value for many activities, such as advertising and viral marketing …
network posts is of great value for many activities, such as advertising and viral marketing …
A new crowdsourcing model to assess disaster using microblog data in typhoon Haiyan
Q Deng, Y Liu, H Zhang, X Deng, Y Ma - Natural Hazards, 2016 - Springer
Risk prediction and damage assessment play critical roles in disaster response to reduce
losses. Social media can serve as crowdsourcing platforms for disaster information …
losses. Social media can serve as crowdsourcing platforms for disaster information …
A data constrained approach for brain tumour detection using fused deep features and SVM
The identification of MR images of the brain with tumours is one of the most critical tasks of
any brain tumour (BT) detection system. Interestingly, because of its non-invasive image …
any brain tumour (BT) detection system. Interestingly, because of its non-invasive image …
Feature selection using Benford's law to support detection of malicious social media bots
The increased amount of high-dimensional imbalanced data in online social networks
challenges existing feature selection methods. Although feature selection methods such as …
challenges existing feature selection methods. Although feature selection methods such as …