IndDoc: an aid for the back-of-the-book indexer

Zargayouna, Haïfa; Mekki, Touria Aït El; Audibert, Laurent; Nazarenko, Adeline

doi:10.3828/indexer.2006.33

Cited by 3 publications

(3 citation statements)

References 3 publications

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“…The papers [7,15] describe subject indexing systems that rely on linguistic rules for term extraction, but their performance is not evaluated. The rules of InDoc system [15] specify various grammatical structures of multi-word terms and their text variants encountered in the text. Since these rules were elaborated for corpus-based terminology extraction, they most likely do not have high efficiency.…”

Section: Related Workmentioning

confidence: 99%

“…In order to extract terms and term definitions with high degree of reliability, we have elaborated a collection of lexico-syntactic patters and rules, and then we have evaluated it in two applied tasks. Our rule-based approach is somewhat close to that in [15], but differs in collections of rules, extraction strategies, and applied tools.…”

Section: Related Workmentioning

confidence: 99%

“…Subject, or back-of-the-book index usually contains significant terms from a particular document together with page numbers where they are used. Similar to computer-aided constructing of glossaries, automatic back-of-the-book indexing [5][6][7][14][15] is a little-researched area with the central problem of selecting relevant terms from a given text document.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Terminological Information Extraction from Russian Scientific Texts: Methods and Applications

Bolshakova¹,

Efremova²,

Ivanov³

EPiC Series in Language and Linguistics

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Scientific texts contain a lot of special terms, which together with their definitions present an important part of scientific knowledge to be extract- ed for various applications, such as text summarization, construction of glossaries and ontologies and so on. The paper reports rule-based methods developed for extracting terminological information involving recognition of term definitions, as well as detection of term occurrences within scientific or technical texts. In contrast to corpus-based terminology extraction, the developed methods are oriented to processing a single text and are based on lexico-syntactic patterns and rules representing specific linguistic information about terms in scientific texts. The formal language LSPL for specification of the patterns and rules is briefly characterized, which is supported with programming tools and used for information extraction. Two applications of the methods are discussed: formation of glossary for a given text document and subject index construction. For these applications, both collections of LSPL patterns and extraction strategies are described, and results of their experimental evaluation are given.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%