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On the Use of Matrix Bloom Filters in Data Leak Protection Read chapter Read first chapter

2018 | OriginalPaper | Chapter

Dense Semantic Graph and Its Application in Single Document Summarisation

Authors : Monika Joshi, Hui Wang, Sally McClean

Published in: Emerging Ideas on Information Filtering and Retrieval

Publisher: Springer International Publishing

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Abstract

Semantic graph representation of text is an important part of natural language processing applications such as text summarisation. We have studied two ways of constructing the semantic graph of a document from dependency parsing of its sentences. The first graph is derived from the subject-object-verb representation of sentence, and the second graph is derived from considering more dependency relations in the sentence by a shortest distance dependency path calculation, resulting in a dense semantic graph. We have shown through experiments that dense semantic graphs gives better performance in semantic graph based unsupervised extractive text summarisation.

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Footnotes
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Metadata
Title
Dense Semantic Graph and Its Application in Single Document Summarisation
Authors
Monika Joshi
Hui Wang
Sally McClean
Copyright Year
2018
Book
Emerging Ideas on Information Filtering and Retrieval

Print ISBN: 978-3-319-68390-4

Electronic ISBN: 978-3-319-68392-8

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-68392-8_4

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