Search Results for author:
Found 12 papers, 4 papers with code
End-to-end multi-particle reconstruction in high occupancy imaging calorimeters with graph neural networks
We present an end-to-end reconstruction algorithm to build particle candidates from detector hits in next-generation granular calorimeters similar to that foreseen for the high-luminosity upgrade of the CMS detector.
Parsing AUC result-figures in machine learning specific scholarly documents for semantically-enriched summarization
Using over 12, 000 figures extracted from 1000 scholarly documents, we show that figure specialized summaries contain more enriched terms about figure semantics.
Sentiment analysis for Urdu online reviews using deep learning models
The objectives of this work are bifold (a) the creation of a human-annotated corpus for the research of sentiment analysis in Urdu; and (b) measurement of up-to-date model performance using a corpus.
Ranked #1 on
Sentiment Analysis
on Urdu Online Reviews
Analysing the impact of global demographic characteristics over the COVID-19 spread using class rule mining and pattern matching
Since the coronavirus disease (COVID-19) outbreak in December 2019, studies have been addressing diverse aspects in relation to COVID-19 and Variant of Concern 202012/01 (VOC 202012/01) such as potential symptoms and predictive tools.
A Decade of In-text Citation Analysis based on Natural Language Processing and Machine Learning Techniques: An overview of empirical studies
Citation analysis is one of the most frequently used methods in research evaluation.
HTSS: A Novel Hybrid Text Summarisation and Simplification Architecture
Our results show that our proposed HTSS model outperforms neural text simplification (NTS) on SARI score and abstractive text summarisation (ATS) on the ROUGE score.
Ranked #2 on
Text Simplification
on EurekaAlert
Exploring Transfer Learning and Domain Data Selection for the Biomedical Translation
Transfer Learning and Selective data training are two of the many approaches being extensively investigated to improve the quality of Neural Machine Translation systems.
Neural Text Simplification of Clinical Letters with a Domain Specific Phrase Table
We also show improvement against baselines including the original text (2. 79) and using the phrase table without the neural text simplification software (2. 94).
Potentially Guided Bidirectionalized RRT* for Fast Optimal Path Planning in Cluttered Environments
The proposed algorithms greatly improve the convergence rate and have a more efficient memory utilization.
ECO-AMLP: A Decision Support System using an Enhanced Class Outlier with Automatic Multilayer Perceptron for Diabetes Prediction
The outlier technique used in our framework gave better results as compared to other pre-processing and classification techniques.
Identification of Manner in Bio-Events
Until recently, these corpora, and hence the event extraction systems trained on them, focussed almost exclusively on the identification and classification of event arguments, without taking into account how the textual context of the events could affect their interpretation.
