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Review of Text Reduction Algorithms and Text Reduction using Sentence Vectorization

by Sneh Garg, Sunil Chhillar
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 107 - Number 12
Year of Publication: 2014
Authors: Sneh Garg, Sunil Chhillar

Sneh Garg, Sunil Chhillar . Review of Text Reduction Algorithms and Text Reduction using Sentence Vectorization. International Journal of Computer Applications. 107, 12 ( December 2014), 39-42. DOI=10.5120/18806-0380

@article{ 10.5120/18806-0380,
author = { Sneh Garg, Sunil Chhillar },
title = { Review of Text Reduction Algorithms and Text Reduction using Sentence Vectorization },
journal = { International Journal of Computer Applications },
issue_date = { December 2014 },
volume = { 107 },
number = { 12 },
month = { December },
year = { 2014 },
issn = { 0975-8887 },
pages = { 39-42 },
numpages = {9},
url = { },
doi = { 10.5120/18806-0380 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-06T22:40:54.639458+05:30
%A Sneh Garg
%A Sunil Chhillar
%T Review of Text Reduction Algorithms and Text Reduction using Sentence Vectorization
%J International Journal of Computer Applications
%@ 0975-8887
%V 107
%N 12
%P 39-42
%D 2014
%I Foundation of Computer Science (FCS), NY, USA

The reduced text of a document is the collection of sentences that contains the important sentences containing keywords of the document. The authentic keywords extraction is the primary target for any text reduction algorithm. The presented survey shows the primary algorithm used for document summarization based on keywords. Also, the work presents a novel approach for keywords identification and in turn text reduction based on words histogram, the no. of sentences containing the words and knowledge corpus. The text summary is extracted using the sentence vectorization process. The sentence vectorization gives the sentences that have at least one of the key words in the sentence from the entire document. The algorithm works fine for the textual matter in the document in MS Notepad format. Factual information that is normally covered under double inverted comas is also given due attention in text summary.

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Index Terms

Computer Science
Information Sciences


Text Reduction Text summary Sentence Vectorization Word Histogram Reduction algorithm Synonyms