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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Golub, K. |
| Copyright Year | 2006 |
| Description | Author affiliation: Dept. of Inf. Technol., Lund Univ. (Golub, K.) |
| 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 |
| Sponsorship | IEEE Comput. Soc. WIC ACM |
| Starting Page | 961 |
| Ending Page | 965 |
| File Size | 202065 |
| Page Count | 5 |
| File Format | |
| ISBN | 0769527477 |
| DOI | 10.1109/WI.2006.169 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2006-12-18 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Vocabulary Gases Databases Abstracts Automatic control Mechanical variables measurement Solids Thesauri Colon Information technology |
| Content Type | Text |
| Resource Type | Article |
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