Abstract
In this work, we investigate the role of morphology on the performance of semantic similarity for morphologically rich languages, such as German and Greek. The challenge in processing languages with richer morphology than English, lies in reducing estimation error while addressing the semantic distortion introduced by a stemmer or a lemmatiser. For this purpose, we propose a methodology for selective stemming, based on a semantic distortion metric. The proposed algorithm is tested on the task of similarity estimation between words using two types of corpus-based similarity metrics: co-occurrence-based and context-based. The performance on morphologically rich languages is boosted by stemming with the context-based metric, unlike English, where the best results are obtained by the co-occurrence-based metric. A key finding is that the estimation error reduction is different when a word is used as a feature, rather than when it is used as a target word.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 9th International Conference on Language Resources and Evaluation, LREC 2014 |
| Editors | Nicoletta Calzolari, Khalid Choukri, Sara Goggi, Thierry Declerck, Joseph Mariani, Bente Maegaard, Asuncion Moreno, Jan Odijk, Helene Mazo, Stelios Piperidis, Hrafn Loftsson |
| Publisher | European Language Resources Association (ELRA) |
| Pages | 1642-1648 |
| Number of pages | 7 |
| ISBN (Electronic) | 9782951740884 |
| Publication status | Published - 2014 |
| Externally published | Yes |
| Event | 9th International Conference on Language Resources and Evaluation, LREC 2014 - Reykjavik, Iceland Duration: 26 May 2014 → 31 May 2014 |
Conference
| Conference | 9th International Conference on Language Resources and Evaluation, LREC 2014 |
|---|---|
| Country/Territory | Iceland |
| City | Reykjavik |
| Period | 26/05/14 → 31/05/14 |
Keywords
- Distributional semantic models
- Lexical semantics
- Morphologically rich languages
- Morphology