Automatic Extraction of Document Topics

Maria Rita Sarmento de Almeida Ribeiro

doi:10.1007/978-3-642-19170-1_11

Automatic Extraction of Document Topics

Maria Rita Sarmento de Almeida Ribeiro

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

10 Citations (Scopus)

Abstract

A keyword or topic for a document is a word or multi-word (sequence of 2 or more words) that summarizes in itself part of that document content. In this paper we compare several statistics-based language independent methodologies to automatically extract keywords. We rank words, multi-words, and word prefixes (with fixed length: 5 characters), by using several similarity measures (some widely known and some newly coined) and evaluate the results obtained as well as the agreement between evaluators. Portuguese, English and Czech were the languages experimented.

Original language	Unknown
Title of host publication	IFIP Advances in Information and Communication Technology
Editors	LM Camarinha-Matos
Publisher	IFIP ( Austria )
Pages	101-108
ISBN (Print)	978-3-642-19170-1
DOIs	https://doi.org/10.1007/978-3-642-19170-1_11
Publication status	Published - 1 Jan 2011
Event	DoCEIS’11 – 2nd Edition of the Doctoral Conference on Computing, Electrical and Industrial Systems - Duration: 1 Jan 2010 → …

Conference

Conference	DoCEIS’11 – 2nd Edition of the Doctoral Conference on Computing, Electrical and Industrial Systems
Period	1/01/10 → …

Access to Document

10.1007/978-3-642-19170-1_11

Cite this

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title = "Automatic Extraction of Document Topics",

abstract = "A keyword or topic for a document is a word or multi-word (sequence of 2 or more words) that summarizes in itself part of that document content. In this paper we compare several statistics-based language independent methodologies to automatically extract keywords. We rank words, multi-words, and word prefixes (with fixed length: 5 characters), by using several similarity measures (some widely known and some newly coined) and evaluate the results obtained as well as the agreement between evaluators. Portuguese, English and Czech were the languages experimented.",

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N2 - A keyword or topic for a document is a word or multi-word (sequence of 2 or more words) that summarizes in itself part of that document content. In this paper we compare several statistics-based language independent methodologies to automatically extract keywords. We rank words, multi-words, and word prefixes (with fixed length: 5 characters), by using several similarity measures (some widely known and some newly coined) and evaluate the results obtained as well as the agreement between evaluators. Portuguese, English and Czech were the languages experimented.

AB - A keyword or topic for a document is a word or multi-word (sequence of 2 or more words) that summarizes in itself part of that document content. In this paper we compare several statistics-based language independent methodologies to automatically extract keywords. We rank words, multi-words, and word prefixes (with fixed length: 5 characters), by using several similarity measures (some widely known and some newly coined) and evaluate the results obtained as well as the agreement between evaluators. Portuguese, English and Czech were the languages experimented.

KW - prefixes

KW - multi-words

KW - words

KW - suffix arrays

KW - Document topics

KW - automatic extraction

U2 - 10.1007/978-3-642-19170-1_11

DO - 10.1007/978-3-642-19170-1_11

M3 - Conference contribution

SN - 978-3-642-19170-1

SP - 101

EP - 108

BT - IFIP Advances in Information and Communication Technology

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PB - IFIP ( Austria )

T2 - DoCEIS’11 – 2nd Edition of the Doctoral Conference on Computing, Electrical and Industrial Systems

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ER -