Search Results for author:
Found 19 papers, 4 papers with code
Calculating the similarity between words and sentences using a lexical database and corpus statistics
To calculate the semantic similarity between words and sentences, the proposed method follows an edge-based approach using a lexical database.
TweetBERT: A Pretrained Language Representation Model for Twitter Text Analysis
Moreover, there is no existing language representation models for text analysis specific to the social media domain.
CAMS: An Annotated Corpus for Causal Analysis of Mental Health Issues in Social Media Posts
We introduce a new dataset for Causal Analysis of Mental health issues in Social media posts (CAMS).
An Annotated Dataset for Explainable Interpersonal Risk Factors of Mental Disturbance in Social Media Posts
With a surge in identifying suicidal risk and its severity in social media posts, we argue that a more consequential and explainable research is required for optimal impact on clinical psychology practice and personalized mental healthcare.
SafeRNet: Safe Transportation Routing in the era of Internet of Vehicles and Mobile Crowd Sensing
This paper proposes SafeRNet, a safe route computation framework which takes advantage of these technologies to analyze streaming traffic data and historical data to effectively infer safe routes and deliver them back to users in real time.
Similarity between Learning Outcomes from Course Objectives using Semantic Analysis, Blooms taxonomy and Corpus statistics
This research introduces the development of semantic similarity algorithms to calculate the similarity between two learning objectives of the same domain.
A Supervised Learning Approach For Heading Detection
As the Portable Document Format (PDF) file format increases in popularity, research in analysing its structure for text extraction and analysis is necessary.
Utilizing Deep Learning to Identify Drug Use on Twitter Data
The collection and examination of social media has become a useful mechanism for studying the mental activity and behavior tendencies of users.
Evolution of Semantic Similarity -- A Survey
Estimating the semantic similarity between text data is one of the challenging and open research problems in the field of Natural Language Processing (NLP).
A Survey on Text Simplification
Text Simplification (TS) aims to reduce the linguistic complexity of content to make it easier to understand.
A summary of the prevalence of Genetic Algorithms in Bioinformatics from 2015 onwards
In recent years, machine learning has seen an increasing presencein a large variety of fields, especially in health care and bioinformatics. More specifically, the field where machine learning algorithms have found most applications is Genetic Algorithms. The objective of this paper is to conduct a survey of articles published from 2015 onwards that deal with Genetic Algorithms(GA) and how they are used in bioinformatics. To achieve the objective, a scoping review was conducted that utilized Google Scholar alongside Publish or Perish and the Scimago Journal & CountryRank to search for respectable sources.
The Homophily Principle in Social Network Analysis
In recent years, social media has become a ubiquitous and integral part of social networking.
Comparative analysis of word embeddings in assessing semantic similarity of complex sentences
Further, we perform a comparative analysis of the performance of various word embeddings and language models on the existing benchmark datasets and the proposed dataset.
Automating Transfer Credit Assessment in Student Mobility -- A Natural Language Processing-based Approach
The proposed model uses a clustering-inspired methodology based on knowledge-based semantic similarity measures to assess the taxonomic similarity of LOs and a transformer-based semantic similarity model to assess the semantic similarity of the LOs.
AdCOFE: Advanced Contextual Feature Extraction in Conversations for emotion classification
Emotion recognition in conversations is an important step in various virtual chat bots which require opinion-based feedback, like in social media threads, online support and many more applications.
Collision Detection: An Improved Deep Learning Approach Using SENet and ResNext
In recent days, with increased population and traffic on roadways, vehicle collision is one of the leading causes of death worldwide.
A Survey on Automated Sarcasm Detection on Twitter
Automatic sarcasm detection is a growing field in computer science.
NODDLE: Node2vec based deep learning model for link prediction
Computing the probability of an edge's existence in a graph network is known as link prediction.
Augmenting Reddit Posts to Determine Wellness Dimensions impacting Mental Health
Amid ongoing health crisis, there is a growing necessity to discern possible signs of Wellness Dimensions (WD) manifested in self-narrated text.
