Titlebook: Computational Linguistics and IntelligentText Processing; 20th International C Alexander Gelbukh Conference proceedings 2023 Springer Natur

output

流眼淚

Antarctic

https://doi.org/10.1007/978-3-540-38441-0atabases, such as GenBank?[.], however, information provided in these databases are usually limited to the country or state level. More fine-grained localization information requires phylogeographers to manually read relevant scientific articles. In this work we propose an approach to automate the p

燦爛

https://doi.org/10.1007/978-3-540-38441-0raining data that contains annotated named entities. However, it is expensive to construct such training data for low-resource domains. In this paper, we propose a recognizer that uses not only training data but also a domain specific dictionary that is available and easy to use. Our recognizer firs

Chagrin

無禮回復(fù)

CYN

絕種

https://doi.org/10.1007/978-3-540-38441-0s. Semantic divergence in related languages is a key concern of historical linguistics. In this paper we investigate semantic divergence across languages by measuring the semantic similarity of cognate sets in multiple languages. The method that we propose is based on cross-lingual word embeddings.

allude

CRAMP