| Revue: | Computación y sistemas |
| Base de datos: | |
| Número de sistema: | 000560718 |
| ISSN: | 1405-5546 |
| Autores: | Bar, Kfir1 Dershowitz, Nachum2 Dankin, Lena2 |
| Instituciones: | 1The College of Management, School of Computer Science, Israel 2Tel Aviv University, School of Computer Science, Israel |
| Año: | 2022 |
| Periodo: | Jul-Sep |
| Volumen: | 26 |
| Número: | 3 |
| Paginación: | 1301-1311 |
| País: | México |
| Idioma: | Inglés |
| Resumen en inglés | We suggest a model for metaphor interpretation using word embeddings trained over a relatively large corpus. Our system handles nominal metaphors, like time is money. It generates a ranked list of potential interpretations of given metaphors. Candidate meanings are drawn from collocations of the topic (time) and vehicle (money) components, automatically extracted from a dependency-parsed corpus. We explore adding candidates derived from word association norms (common human responses to cues). Our ranking procedure considers similarity between candidate interpretations and metaphor components, measured in a semantic vector space. Lastly, a clustering algorithm removes semantically related duplicates, thereby allowing other candidate interpretations to attain higher rank. We evaluate using different sets of annotated metaphors, with encouraging preliminary results. |
| Keyword: | Metaphor interpretation, Word embeddings |
| Texte intégral: | Texto completo (Ver HTML) Texto completo (Ver PDF) |
