Automatic term recognition based on statistics of compound nouns and their components
Bibliographic Data
| ID | 20395332 |
|---|---|
| Authors | Hiroshi Nakagawa (0000-0001-9368-519X, The University of Tokyo), Tatsunori Mori (0000-0003-0656-6518, Yokohama National University) |
| Year | 2003 |
| Volume | 9 |
| Issue | 2 |
| Pages | 201-219 |
| Publication date | 2003-12-31 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Terminology International Journal of Theoretical and Applied Issues in Specialized Communication (JOURNAL) |
| Journal identifiers | ISSN: 0929-9971 • E-ISSN: 1569-9994 |
| Publisher | John Benjamins Publishing Company (PUBLISHER • NL) |
| DOI | 10.1075/term.9.2.04nak |
| OpenAlex | W2031203571 |
| Language | EN |
| Citations received | 4 |
| References cited | 4 |
In this paper, we propose a new approach to enhance automatic recognition systems for domain-specific terms. The approach is based on the statistics about the relation between a compound noun and its constituents that are simple nouns. More precisely, we focus on how many nouns adjoin the noun in question to form compound nouns. We propose several scoring methods based on this approach and experimentally evaluate them on the NTCIR1 TMREC test collection. The results are very promising, especially in low and high recall
Linguistics · Natural language processing · Noun · Proper noun · Recall · Advanced Text Analysis Techniques · Computer Science · Natural Language Processing Techniques · Philosophy · Topic Modeling · Artificial Intelligence
| Citations per year | 0.21 |
|---|---|
| Citation span | 2007 - 2025 (19) |
| Highly cited | No |