Literaturnachweis - Detailanzeige
Autor/inn/en | Krishnaveni, P.; Balasundaram, S. R. |
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Titel | Summarizing Learning Materials Using Graph Based Multi-Document Summarization |
Quelle | In: International Journal of Web-Based Learning and Teaching Technologies, 16 (2021) 5, S.39-57, Artikel 3 (19 Seiten)Infoseite zur Zeitschrift
PDF als Volltext |
Sprache | englisch |
Dokumenttyp | gedruckt; online; Zeitschriftenaufsatz |
ISSN | 1548-1093 |
Schlagwörter | Instructional Materials; Electronic Learning; Documentation; Graphs; Mathematics |
Abstract | The 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. (As Provided). |
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Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
Update | 2024/1/01 |