Summarizing learning materials using graph based multi-document summarization

Simple item page
dc.contributor.authorKrishnaveni, P
dc.contributor.authorBalasundaram, S.R.
dc.date.accessioned2026-11-06T11:13:57Z
dc.date.available2026-11-06T11:13:57Z
dc.date.issued2021-10
dc.description.abstractThe learners and teachers of the teaching-learning process highly depend on online learning systems such as E-learning, which contains huge volumes of electronic contents related to a course. The multi-document summarization (MDS) is useful for summarizing such electronic contents. This article applies the task of MDS in an E-learning context. The objective of this article is threefold: 1) design a generic graph based multi-document summarizer DSGA (Dynamic Summary Generation Algorithm) to produce a variable length (dynamic) summary of academic text based learning materials based on a learner’s request; 2) analyze the summary generation process; 3) perform content-based and task-based evaluations on the generated summary. The experimental results show that the DSGA summarizer performs better than the graph-based summarizers LexRank (LR) and Aggregate Similarity (AS). From the task-based evaluation, it is observed that the generated summary helps the learners to understand and comprehend the materials easily.
dc.identifier.issn15481093
dc.identifier.urihttps://doi.org/10.4018/IJWLTT.20210901.oa3
dc.identifier.urihttp://nitt.ndl.gov.in/handle/123456789/416
dc.language.isoen
dc.publisherIGI Global
dc.relation.ispartofseriesInternational Journal of Web-Based Learning and Teaching Technologies; Vol. 16/ No. 5
dc.titleSummarizing learning materials using graph based multi-document summarization
dc.typeArticle
Files
Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
Summarizing-Learning-Materials-Using-Graph-Based-Multi-Document-Summarization.pdf
Size:
6.39 MB
Format:
Adobe Portable Document Format
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
411 B
Format:
Item-specific license agreed upon to submission
Description:
Download
Collections
Journal Articles