Summary of the paper
| Title | Word Semantic Similarity for Morphologically Rich Languages |
|---|---|
| Authors | Kalliopi Zervanou, Elias Iosif and Alexandros Potamianos |
| 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. |
| Topics | Semantics, Language Modelling |
Full paper  |
Word Semantic Similarity for Morphologically Rich Languages |
| Bibtex | @InProceedings{ZERVANOU14.973, author = {Kalliopi Zervanou and Elias Iosif and Alexandros Potamianos}, title = {Word Semantic Similarity for Morphologically Rich Languages}, booktitle = {Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)}, year = {2014}, month = {may}, date = {26-31}, address = {Reykjavik, Iceland}, editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Hrafn Loftsson and Bente Maegaard and Joseph Mariani and Asuncion Moreno and Jan Odijk and Stelios Piperidis}, publisher = {European Language Resources Association (ELRA)}, isbn = {978-2-9517408-8-4}, language = {english} } |