Author(s):
1. Dr. K. ARUTCHELVAN:
Department of Computer and Information Science, Annamalai University, Chidambaram, Tamil Nadu, India.
2. R. SENTHAMIZH SELVAN:
Department of Computer and Information Science, Annamalai University, Chidambaram, Tamil Nadu, India.
Abstract:
ive MDS using rich semantic graph-based methodology and topic modelling. The proposed approach generates summary by using graph-relations across multiple documents based on the relevant topics. The proposed approach is build using the centrality node ranking technique. The weighted graph ranking technique is applied to obtain the sequence of the sentences. The summary is generated using the highest rank scores of the sentences. The proposed technique is evaluated using the CNN/Daily Mail datasets.
Page(s):
4590-4597
DOI:
DOI not available
Published:
Journal: Journal of Theoretical and Applied Information Technology, Volume: 100, Issue: 12, Year: 2022
Keywords:
similarity measure
,
Topic Modelling
,
Semantic Graph
,
MultiDocument Abstractive Summarization
,
Sentence Ranking
References:
References are not available for this document.
Citations
Citations are not available for this document.