Publication details
Development of HAMOD: a High Agreement Multi-lingual Outlier Detection dataset
| Authors | |
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| Year of publication | 2021 |
| Type | Article in Proceedings |
| Conference | Recent Advances in Slavonic Natural Language Processing (RASLAN 2021) |
| MU Faculty or unit | |
| Citation | |
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| Keywords | HAMOD; Distributional thesaurus; Outlier detection; Word embeddings; Sketch Engine |
| Description | In this paper we describe further development of a High Agreement Multi- lingual Outlier Detection dataset (HAMOD) outlier that is used for the purpose of evaluation of automatic distributional thesauri. We briefly introduce the task and methodological motivation for developing such a dataset, then we present the current status of the dataset and related tools as well as results measured on the dataset so far (both in terms of agreement rates and thesauri eveluation). Finally we discuss future developments of HAMOD. |
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