Question Answer System: A State-of-Art Representation of Quantitative and Qualitative Analysis

Zope, Bhushan; Mishra, Sashikala; Shaw, Kailash; Vora, Deepali; Kotecha, Ketan; Bidwe, Ranjeet Vasant

doi:10.3390/bdcc6040109

Cited by 15 publications

(4 citation statements)

References 152 publications

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“…Secondly, further improvements in the feature extraction methods can be made, and more accurate and efficient techniques can be applied for the extraction of features. Other work in this area shall help address these issues, probably using transfer learning concepts [25].…”

Section: Discussionmentioning

confidence: 99%

Brain Tumor Detection Using Advanced Deep Learning Implementations

Shrotriya,

Agarwal,

Mishra

et al. 2023

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Modern technological advancements are concentrated on the development of intelligent machines or software that mimic and respond like humans. Today's Artificial Intelligence computing activities encompass language processing, perception, learning, planning, and problem-solving. Early cancer detection is essential to saving as many lives as possible. A recent report from the "World Health Organization" (WHO) in February 2018 highlighted mortality associated with brain tumors or the "CNS" (Central Nervous System). This paper primarily aims to detect and predict the presence of brain tumors in individuals using "MRI" (Magnetic Resonance Imaging) brain scan images. This is achieved through machine learning techniques in classification. A model for identifying brain tumors is created using a deep learning algorithm and a dataset comprising thousands of images. "Convolutional Neural Networks" (CNNs) are employed to identify and predict the likelihood of the presence of a brain tumor in an individual, based on the provided MRI scan image. This work explores several potential mechanisms for using deep learning techniques to construct models for brain tumor detection. The objective is to discover more effective methods to detect brain tumors based on MRI scans, thereby enabling neurologists to make decisions with increased ease, accuracy, and speed. Manual classification of brain tumors using only MRI images can be time-consuming, potentially delaying necessary treatment for the affected individual. Therefore, the assistive use of machine learning technology can help healthcare professionals enhance their work in combating brain tumors, a severe medical condition.

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Section: Discussionmentioning

confidence: 99%

Brain Tumor Detection Using Advanced Deep Learning Implementations

Shrotriya,

Agarwal,

Mishra

et al. 2023

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“…Several research has also investigated how well different NLP techniques, including text similarity algorithms and semantic analysis, work to recognise related questions and produce pertinent responses [34], [35]. Other studies have concentrated on using machine learning methods, like support vector machines and random forests, to categorise queries and find pertinent solutions [36] [37].…”

Section: Related Workmentioning

confidence: 99%

A systematic review of similar Questions Retrieval Approaches

Khodke,

Dhande

2023

AJCT

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A renowned online community known as Quora enables members to post queries, receive insightful responses, and share knowledge. The capacity of Quora to find related questions based on a user's search is a distinctive feature that makes it simple for users to access pertinent information and add it to the platform's knowledge base. The retrieval of comparable questions from Quora is the topic of this paper. We assess various systems that classify related queries and quickly deliver pertinent responses to information searchers. Our assessment of machine learning and natural language processing methods focuses on how well these methods work when obtaining queries from the large Quora question database that serves related objectives. Our thorough research paper provides a summary of the literature on comparable question retrieval in Quora while highlighting the benefits and drawbacks of various approaches. Our evaluation identifies prospective topics for more research and development and acts as a guide for future scholars interested in this field. By enhancing similar question retrieval on Quora, we hope to encourage knowledge-sharing and community development on this important platform. Users can find the most pertinent responses to their inquiries on Quora by using the study's findings.

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“…The way that systems based on knowledge handle difficulties may differ since some systems encode professional expertise as rules, while others employ a case-based reasoning [78]. To accurately respond to customer inquiries, QA systems combine natural language processing, information retrieval, logical reasoning, knowledge representation, and machine learning [79]. Although knowledge-based approaches are a crucial part of QA systems, they do have significant drawbacks.…”

Section: Critical Analysismentioning

confidence: 99%

Deep Learning Based Question Answering System (Survey)

Saeed,

ashraf,

Jhanjhi

2023

Preprint

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Deep learning-based question answering systems have transformed the discipline of natural language processing (NLP) by automating the extraction of answers from textual data. This survey paper provides a captivating overview of these systems, exploring methodologies, techniques, and architectures such as recurrent neural networks (RNNs), BERT model, and transformer models. Extractive and generative approaches are examined, alongside the challenges of handling complex questions, managing noisy input, and addressing rare or unseen words. This survey serves as a stimulating reference, offering valuable insights to researchers and practitioners, fueling innovation and advancement in question answering systems within NLP.

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Question Answer System: A State-of-Art Representation of Quantitative and Qualitative Analysis

Cited by 15 publications

References 152 publications

Brain Tumor Detection Using Advanced Deep Learning Implementations

Brain Tumor Detection Using Advanced Deep Learning Implementations

A systematic review of similar Questions Retrieval Approaches

Deep Learning Based Question Answering System (Survey)

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