Saurabh Raj Sangwan
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View article: Natural language processing as Digital Veda (डजटल वद): a humanistic framework for language, ethics, and AI
Natural language processing as Digital Veda (डजटल वद): a humanistic framework for language, ethics, and AI Open
This article conceptualizes Natural Language Processing (NLP) as the Digital Veda (डिजिटल वेद), framing it as a culturally rooted communicative infrastructure inspired by the Vedic tradition of structured knowledge preservation and ethical…
View article: SIGMA: Modelling Toxic Stance and Ideological Diffusion in Reddit's Manosphere Using Psychographic and Linguistic Signals
SIGMA: Modelling Toxic Stance and Ideological Diffusion in Reddit's Manosphere Using Psychographic and Linguistic Signals Open
View article: SENS-HEAD: A Machine Learning Framework for Sensationalism Detection in News Headlines Using Linguistic and Semantic Features
SENS-HEAD: A Machine Learning Framework for Sensationalism Detection in News Headlines Using Linguistic and Semantic Features Open
The proliferation of sensationalized news headlines has raised concerns about media integrity, necessitating automated approaches for detecting sensationalism beyond traditional clickbait classification. This study presents SENS-HEAD, a no…
View article: SleepDepNet: A Multi-Task Transformer Framework for Assessing Sleep Quality and Depression Risk from Social Media Narratives
SleepDepNet: A Multi-Task Transformer Framework for Assessing Sleep Quality and Depression Risk from Social Media Narratives Open
The bidirectional relationship between sleep disturbances and depression presents a serious challenge for digital mental health research and intervention. This study introduces SleepDepNet , a transformer-based multi-task learning model de…
View article: Improving Depression Detection Through Biomedical Entity Linking: A Hybrid Approach Using Embedding Models and Full-Text Search
Improving Depression Detection Through Biomedical Entity Linking: A Hybrid Approach Using Embedding Models and Full-Text Search Open
View article: Enhancing drug discovery and patient care through advanced analytics with the power of NLP and machine learning in pharmaceutical data interpretation
Enhancing drug discovery and patient care through advanced analytics with the power of NLP and machine learning in pharmaceutical data interpretation Open
This study delves into the transformative potential of Machine Learning (ML) and Natural Language Processing (NLP) within the pharmaceutical industry, spotlighting their significant impact on enhancing medical research methodologies and op…
View article: Hyper-personalized employment in urban hubs: multimodal fusion architectures for personality-based job matching
Hyper-personalized employment in urban hubs: multimodal fusion architectures for personality-based job matching Open
In the evolving landscape of smart cities, employment strategies have been steering towards a more personalized approach, aiming to enhance job satisfaction and boost economic efficiency. This paper explores an advanced solution by integra…
View article: Improving Depression Detection through Biomedical Entity Linking: A Hybrid Approach Using Embedding Models and Full-Text Search
Improving Depression Detection through Biomedical Entity Linking: A Hybrid Approach Using Embedding Models and Full-Text Search Open
Depression is a multifaceted mental health disorder that necessitates accurate identification of symptoms, treatments, and comorbidities for effective diagnosis and treatment planning. This paper introduces a hybrid approach to Biomedical …
View article: Transformer-Based Abstractive Summarization for Depression Detection Literature for Enhanced Medical Insights
Transformer-Based Abstractive Summarization for Depression Detection Literature for Enhanced Medical Insights Open
View article: Ontology-Based Natural Language Processing for Sentimental Knowledge Analysis Using Deep Learning Architectures
Ontology-Based Natural Language Processing for Sentimental Knowledge Analysis Using Deep Learning Architectures Open
When tested with popular datasets, sentiment categorization using deep learning (DL) algorithms will produce positive results. Building a corpus on novel themes to train machine learning methods in sentiment classification with high assura…
View article: Rumour detection using deep learning and filter-wrapper feature selection in benchmark twitter dataset
Rumour detection using deep learning and filter-wrapper feature selection in benchmark twitter dataset Open
Microblogs have become a customary news media source in recent times. But as synthetic text or 'readfakes' scale up the online disinformation operation, unsubstantiated pieces of information on social media platforms can cause signi…
View article: Denigration Bullying Resolution using Wolf Search Optimized Online Reputation Rumour Detection
Denigration Bullying Resolution using Wolf Search Optimized Online Reputation Rumour Detection Open
Denigration is the most common bullying tactic involving public figures like celebrities and politicians where rumourous stories, pictures and videos are posted online to discredit and defame. It involves online “dissing” or “gossiping” ab…
View article: Supervised Machine Learning Based Buyer’s Bidding Behaviour Detection in Online Auction
Supervised Machine Learning Based Buyer’s Bidding Behaviour Detection in Online Auction Open
In this era of burgeoning online commerce, online auction serves as a platform for sellers and buyers to associate with each other. In spite of popularity of online auctions, it involves some suspicious bidding behaviours that deviate from…
View article: Sarcasm Detection Using Soft Attention-Based Bidirectional Long Short-Term Memory Model With Convolution Network
Sarcasm Detection Using Soft Attention-Based Bidirectional Long Short-Term Memory Model With Convolution Network Open
A large community of research has been developed in recent years to analyze social media and social networks, with the aim of understanding, discovering insights, and exploiting the available information. The focus has shifted from convent…
View article: A Particle Swarm Optimized Learning Model of Fault Classification in Web-Apps
A Particle Swarm Optimized Learning Model of Fault Classification in Web-Apps Open
The term web-app defines the current dynamic pragmatics of the website, where the user has control. Finding faults in such dynamic content is challenging, as to whether the fault is exposed or not depends on its execution path. Moreover, t…
View article: Expert Finding in Community Question-Answering for Post Recommendation
Expert Finding in Community Question-Answering for Post Recommendation Open
Community question answering system is a perfect example of platform where people participate to seek expertise on their topic of interest. But information overload, finding the expertise level of users and trustworthy answers remain key c…