Search Results for author:
Found 13 papers, 5 papers with code
Divide and Conquer: From Complexity to Simplicity for Lay Summarization
We describe our approach for the 1st Computational Linguistics Lay Summary Shared Task CL-LaySumm20.
NMF Ensembles? Not for Text Summarization!
Non-negative Matrix Factorization (NMF) has been used for text analytics with promising results.
Human Centered AI for Indian Legal Text Analytics
Legal research is a crucial task in the practice of law.
Infusing Knowledge into Large Language Models with Contextual Prompts
Knowledge infusion is a promising method for enhancing Large Language Models for domain-specific NLP tasks rather than pre-training models over large data from scratch.
Deep dive into language traits of AI-generated Abstracts
Generative language models, such as ChatGPT, have garnered attention for their ability to generate human-like writing in various fields, including academic research.
I Want This, Not That: Personalized Summarization of Scientific Scholarly Texts
In this paper, we present a proposal for an unsupervised algorithm, P-Summ, that generates an extractive summary of scientific scholarly text to meet the personal knowledge needs of the user.
Quantitative Discourse Cohesion Analysis of Scientific Scholarly Texts using Multilayer Networks
We use a publicly available dataset along with a curated set of contrasting examples to validate the proposed metrics by comparing them against select indices computed using existing cohesion analysis tools.
Investigating Entropy for Extractive Document Summarization
Ergo, informativeness is the prime attribute of document summary generated by an algorithm, and selecting sentences that capture the essence of a document is the primary goal of extractive document summarization.
Similar Cases Recommendation using Legal Knowledge Graphs
A legal knowledge graph constructed from court cases, judgments, laws and other legal documents can enable a number of applications like question answering, document similarity, and search.
Complex Network based Supervised Keyword Extractor
This shows that the proposed method is independent of the domain, collection, and language of the training corpora.
Semi-automatic System for Title Construction
We further establish empirically that the proposed approach can be applied to any text irrespective of the training domain and corpus.
sCAKE: Semantic Connectivity Aware Keyword Extraction
Combination of the proposed graph construction and scoring methods leads to a novel, parameterless keyword extraction method (sCAKE) based on semantic connectivity of words in the document.
Results from the Supernova Photometric Classification Challenge
A spectroscopically confirmed subset was provided for training.
Cosmology and Nongalactic Astrophysics
