Word semantic similarity for morphologically rich languages

Kalliopi Zervanou; Elias Iosif; Alexandros Potamianos

Word semantic similarity for morphologically rich languages

Kalliopi Zervanou, Elias Iosif, Alexandros Potamianos

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

11 Citations (Scopus)

57 Downloads (Pure)

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

Funding

Elias Iosif and Alexandros Potamianos were partially funded by the EU-IST FP7 PortDial project (“Language Resources for Portable Multilingual Spoken Dialog Systems”), grant number 296170. The authors wish to thank Maria Giannoudaki for the development of the Greek evaluation dataset and preliminary experiments, and Ioannis Klasinas for corpora creation.

Keywords

Distributional semantic models
Lexical semantics
Morphologically rich languages
Morphology

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Zervanou, K., Iosif, E., & Potamianos, A. (2014). Word semantic similarity for morphologically rich languages. In N. Calzolari, K. Choukri, S. Goggi, T. Declerck, J. Mariani, B. Maegaard, A. Moreno, J. Odijk, H. Mazo, S. Piperidis, & H. Loftsson (Eds.), Proceedings of the 9th International Conference on Language Resources and Evaluation, LREC 2014 (pp. 1642-1648). European Language Resources Association (ELRA).

Zervanou, Kalliopi ; Iosif, Elias ; Potamianos, Alexandros. / Word semantic similarity for morphologically rich languages. Proceedings of the 9th International Conference on Language Resources and Evaluation, LREC 2014. editor / Nicoletta Calzolari ; Khalid Choukri ; Sara Goggi ; Thierry Declerck ; Joseph Mariani ; Bente Maegaard ; Asuncion Moreno ; Jan Odijk ; Helene Mazo ; Stelios Piperidis ; Hrafn Loftsson. European Language Resources Association (ELRA), 2014. pp. 1642-1648

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title = "Word semantic similarity for morphologically rich languages",

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.",

keywords = "Distributional semantic models, Lexical semantics, Morphologically rich languages, Morphology",

author = "Kalliopi Zervanou and Elias Iosif and Alexandros Potamianos",

year = "2014",

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editor = "Nicoletta Calzolari and Khalid Choukri and Sara Goggi and Thierry Declerck and Joseph Mariani and Bente Maegaard and Asuncion Moreno and Jan Odijk and Helene Mazo and Stelios Piperidis and Hrafn Loftsson",

booktitle = "Proceedings of the 9th International Conference on Language Resources and Evaluation, LREC 2014",

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Zervanou, K, Iosif, E & Potamianos, A 2014, Word semantic similarity for morphologically rich languages. in N Calzolari, K Choukri, S Goggi, T Declerck, J Mariani, B Maegaard, A Moreno, J Odijk, H Mazo, S Piperidis & H Loftsson (eds), Proceedings of the 9th International Conference on Language Resources and Evaluation, LREC 2014. European Language Resources Association (ELRA), pp. 1642-1648, 9th International Conference on Language Resources and Evaluation, LREC 2014, Reykjavik, Iceland, 26/05/14.

Word semantic similarity for morphologically rich languages. / Zervanou, Kalliopi; Iosif, Elias; Potamianos, Alexandros.
Proceedings of the 9th International Conference on Language Resources and Evaluation, LREC 2014. ed. / Nicoletta Calzolari; Khalid Choukri; Sara Goggi; Thierry Declerck; Joseph Mariani; Bente Maegaard; Asuncion Moreno; Jan Odijk; Helene Mazo; Stelios Piperidis; Hrafn Loftsson. European Language Resources Association (ELRA), 2014. p. 1642-1648.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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T1 - Word semantic similarity for morphologically rich languages

AU - Zervanou, Kalliopi

AU - Iosif, Elias

AU - Potamianos, Alexandros

PY - 2014

Y1 - 2014

N2 - 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.

AB - 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.

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KW - Lexical semantics

KW - Morphologically rich languages

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BT - Proceedings of the 9th International Conference on Language Resources and Evaluation, LREC 2014

A2 - Calzolari, Nicoletta

A2 - Choukri, Khalid

A2 - Goggi, Sara

A2 - Declerck, Thierry

A2 - Mariani, Joseph

A2 - Maegaard, Bente

A2 - Moreno, Asuncion

A2 - Odijk, Jan

A2 - Mazo, Helene

A2 - Piperidis, Stelios

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PB - European Language Resources Association (ELRA)

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ER -

Zervanou K, Iosif E, Potamianos A. Word semantic similarity for morphologically rich languages. In Calzolari N, Choukri K, Goggi S, Declerck T, Mariani J, Maegaard B, Moreno A, Odijk J, Mazo H, Piperidis S, Loftsson H, editors, Proceedings of the 9th International Conference on Language Resources and Evaluation, LREC 2014. European Language Resources Association (ELRA). 2014. p. 1642-1648

Word semantic similarity for morphologically rich languages

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