The role of different thesauri terms and captions in automated subject classification

Koraljka Golub

doi:10.1109/WI.2006.169

The role of different thesauri terms and captions in automated subject classification

Koraljka Golub

Institutionen för elektro- och informationsteknik

Forskningsoutput: Kapitel i bok/rapport/Conference proceeding › Konferenspaper i proceeding › Peer review

Sammanfattning

The paper aims to explore to what degree different types of terms in engineering information (Ei) thesaurus and classification scheme influence automated subject classification performance. Preferred terms, their synonyms, broader, narrower, related terms, and captions are examined in combination with a stemmer and a stop-word list. The algorithm comprises string-to-string matching between words in the documents to be classified and words in term lists derived from the Ei thesaurus and classification scheme. The data collection for evaluation consists of some 35000 scientific paper abstracts from the compendex database. A subset of the Ei thesaurus and classification scheme is used, comprising 92 classes at up to five hierarchical levels from general engineering. The results show that preferred terms perform best, whereas captions perform worst. Stemming in most cases shows performance improvement, whereas the stop-word list does not have a significant impact

Originalspråk	engelska
Titel på värdpublikation	Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence
Förlag	IEEE - Institute of Electrical and Electronics Engineers Inc.
Sidor	961-965
Antal sidor	5
ISBN (tryckt)	0-7695-2747-7
DOI	https://doi.org/10.1109/WI.2006.169
Status	Published - 2006
Evenemang	2006 IEEE/WIC/ACM International Conference on Web Intelligence - Hong Kong, Kina Varaktighet: 2006 dec. 18 → 2006 dec. 22

Konferens

Konferens	2006 IEEE/WIC/ACM International Conference on Web Intelligence
Land/Territorium	Kina
Ort	Hong Kong
Period	2006/12/18 → 2006/12/22

Ämnesklassifikation (UKÄ)

Elektroteknik och elektronik

Tillgång till dokument

10.1109/WI.2006.169

Citera det här

@inproceedings{d0aaf5e32bc84a02b51975040f8d8788,

title = "The role of different thesauri terms and captions in automated subject classification",

abstract = "The paper aims to explore to what degree different types of terms in engineering information (Ei) thesaurus and classification scheme influence automated subject classification performance. Preferred terms, their synonyms, broader, narrower, related terms, and captions are examined in combination with a stemmer and a stop-word list. The algorithm comprises string-to-string matching between words in the documents to be classified and words in term lists derived from the Ei thesaurus and classification scheme. The data collection for evaluation consists of some 35000 scientific paper abstracts from the compendex database. A subset of the Ei thesaurus and classification scheme is used, comprising 92 classes at up to five hierarchical levels from general engineering. The results show that preferred terms perform best, whereas captions perform worst. Stemming in most cases shows performance improvement, whereas the stop-word list does not have a significant impact",

keywords = "thesauri term, automated subject classification, engineering information, string-to-string matching, document classification, compendex database, data collection",

author = "Koraljka Golub",

year = "2006",

doi = "10.1109/WI.2006.169",

language = "English",

isbn = "0-7695-2747-7",

pages = "961--965",

booktitle = "Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence",

publisher = "IEEE - Institute of Electrical and Electronics Engineers Inc.",

address = "United States",

note = "2006 IEEE/WIC/ACM International Conference on Web Intelligence ; Conference date: 18-12-2006 Through 22-12-2006",

}

Golub, K 2006, The role of different thesauri terms and captions in automated subject classification. i Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence. IEEE - Institute of Electrical and Electronics Engineers Inc., s. 961-965, 2006 IEEE/WIC/ACM International Conference on Web Intelligence, Hong Kong, Kina, 2006/12/18. https://doi.org/10.1109/WI.2006.169

The role of different thesauri terms and captions in automated subject classification. / Golub, Koraljka.
Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence. IEEE - Institute of Electrical and Electronics Engineers Inc., 2006. s. 961-965.

Forskningsoutput: Kapitel i bok/rapport/Conference proceeding › Konferenspaper i proceeding › Peer review

TY - GEN

T1 - The role of different thesauri terms and captions in automated subject classification

AU - Golub, Koraljka

PY - 2006

Y1 - 2006

N2 - The paper aims to explore to what degree different types of terms in engineering information (Ei) thesaurus and classification scheme influence automated subject classification performance. Preferred terms, their synonyms, broader, narrower, related terms, and captions are examined in combination with a stemmer and a stop-word list. The algorithm comprises string-to-string matching between words in the documents to be classified and words in term lists derived from the Ei thesaurus and classification scheme. The data collection for evaluation consists of some 35000 scientific paper abstracts from the compendex database. A subset of the Ei thesaurus and classification scheme is used, comprising 92 classes at up to five hierarchical levels from general engineering. The results show that preferred terms perform best, whereas captions perform worst. Stemming in most cases shows performance improvement, whereas the stop-word list does not have a significant impact

AB - The paper aims to explore to what degree different types of terms in engineering information (Ei) thesaurus and classification scheme influence automated subject classification performance. Preferred terms, their synonyms, broader, narrower, related terms, and captions are examined in combination with a stemmer and a stop-word list. The algorithm comprises string-to-string matching between words in the documents to be classified and words in term lists derived from the Ei thesaurus and classification scheme. The data collection for evaluation consists of some 35000 scientific paper abstracts from the compendex database. A subset of the Ei thesaurus and classification scheme is used, comprising 92 classes at up to five hierarchical levels from general engineering. The results show that preferred terms perform best, whereas captions perform worst. Stemming in most cases shows performance improvement, whereas the stop-word list does not have a significant impact

KW - thesauri term

KW - automated subject classification

KW - engineering information

KW - string-to-string matching

KW - document classification

KW - compendex database

KW - data collection

U2 - 10.1109/WI.2006.169

DO - 10.1109/WI.2006.169

M3 - Paper in conference proceeding

SN - 0-7695-2747-7

SP - 961

EP - 965

BT - Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence

PB - IEEE - Institute of Electrical and Electronics Engineers Inc.

T2 - 2006 IEEE/WIC/ACM International Conference on Web Intelligence

Y2 - 18 December 2006 through 22 December 2006

ER -

The role of different thesauri terms and captions in automated subject classification

Sammanfattning

Konferens

Ämnesklassifikation (UKÄ)

Tillgång till dokument

Fingeravtryck

Citera det här