Effective Multimodal Opinion Mining Framework Using Ensemble Learning Technique for Disease Risk Prediction

Aiswaryadevi, V. J.; Kiruthika, S.; Priyanka, G.; Nataraj, N.; Sruthi, M. S.

doi:10.1007/978-981-33-4305-4_67

Cited by 2 publications

(1 citation statement)

References 18 publications

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“…There is no universally applicable solution because the majority of the research in this field focuses on sentencelevel text analysis, treating the work as a general issue without taking into account various sorts of sentences [7]. Deep learning has become popular in recent years and is utilized in numerous applications that carry out complex tasks, including speech recognition methods, facial recognition systems, and object detection, to name a few examples [8]. For many years, the hardware restrictions hindered the widespread adoption of DL techniques.…”

Section: Review Of Literaturementioning

confidence: 99%

5G Network in Content Based Emotion Detection by Sentimental Analysis Integrated with Opinion Mining and Deep Learning Architectures

Gyawali

2022

ijfrcsce

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The rapid growth of social networking sites in the Internet era has made them a necessary tool for sharing emotions with the entire world. To extract emotions from text, a variety of tools and approaches are available in fields of opinion mining as well as sentiment analysis. These researches propose novel technique opinion mining based emotion detection from the input social content using deep learning architectures. Here the input has been obtained as social media content based on opinion miningby 5G networks. The input has been processed for noise removal, smoothening and normalization. This processed input has been segmented using Markov model based convolutional neural networks (MMCNN). The segmented data has been classified using Canonical Correlation AnalysisBayesian neural network.An opinion mining method that analyzes statements regarding computer programming and predicts or recognizes their polarity was implemented, along with an earlier module that was integrated into an intelligent learning environment. These three steps made up the creation of the module. We assessed the corpus, text polarity precision, and emotion recognition. Experimental analysis has been carried out for various social media content collected by opinion mining in terms of accuracy, precision, recall, F-1 score, AUC.Proposed technique attained accuracy of 99%, precision of 96%, recall of 96%, F-1 score of 95%, AUC of 89%.

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Section: Review Of Literaturementioning

confidence: 99%

5G Network in Content Based Emotion Detection by Sentimental Analysis Integrated with Opinion Mining and Deep Learning Architectures

Gyawali

2022

ijfrcsce

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Design of Data Mining Techniques for Online Blood Bank Management by CNN Model

Jacob¹,

Darney²

2021

JUCCT

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A blood bank is the organisation responsible for storing blood to transfuse it to the patients in need. The primary goal of a blood bank is to be reliable and ensure that patients get the relevant non-toxic blood to avoid transfusion-related complications since blood is a critical medicinal resource. It is difficult for the blood banks to offer high levels of precision, dependability, and automation in the blood storage and transfusion process if blood bank administration includes many human processes. This research framework is proposing to maintain blood bank records using CNN model classification method. In the pre-processing of CNN method, the datasets are tokenized and set the donor’s eligibility. It will make it easier for regular blood donors to donate regularly to charitable people and organizations. A few machine learning techniques offer the automated website updation. Jupyter note book has been used to analyze the dataset of blood donors using decision trees, neural networks, and von Bays techniques. The proposed method operates online through a website. Moreover, the donor's eligibility status with gender, body mass index, blood pressure level, and frequency of blood donations is also maintained. Finally, the comparison of different machine learning algorithms with the suggested framework is tabulated.

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Effective Multimodal Opinion Mining Framework Using Ensemble Learning Technique for Disease Risk Prediction

Cited by 2 publications

References 18 publications

5G Network in Content Based Emotion Detection by Sentimental Analysis Integrated with Opinion Mining and Deep Learning Architectures

5G Network in Content Based Emotion Detection by Sentimental Analysis Integrated with Opinion Mining and Deep Learning Architectures

Design of Data Mining Techniques for Online Blood Bank Management by CNN Model

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