A Survey on Domain-Specific Summarization Techniques

Title

A Survey on Domain-Specific Summarization Techniques

Creator

Rajan R.P.; Jose D.V.

Description

Automatic text summarization using different natural language processing techniques (NLP) has gained much momentum in recent years. Text summarization is an intensive process of extracting representative gist of the contents present in a document. Manual summarization of structured and unstructured text is a tedious task that involves immense human effort and time. There are quite a number of successful text summarization algorithms for generic documents. But when it comes specialized for a particular domain, the generic training of algorithms does not suffice the purpose. Hence, context-aware summarization of unstructured and structured text using various algorithms needs specific scoring techniques to supplement the base algorithms. This paper is an attempt to give an overview of methods and algorithms that are used for context-aware summarization of generic texts. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Source

Lecture Notes in Networks and Systems, Vol-318, pp. 351-361.

Date

2022-01-01

Publisher

Springer Science and Business Media Deutschland GmbH

Subject

Abstractive summarization; Extractive summarization; Semantic modelling; Text mining; Text summarization

Coverage

Rajan R.P., Christ Deemed to be University, Karnataka, Bangalore, India; Jose D.V., Christ Deemed to be University, Karnataka, Bangalore, India

Rights

Restricted Access

Relation

ISSN: 23673370; ISBN: 978-981165688-0

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1007/978-981-16-5689-7_31

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