@inproceedings{5cb682b855e047e3b8ff987219c2aa51,
title = "Stemming and segmentation for classical Tibetan",
abstract = "Tibetan is a monosyllabic language for which computerized language tools are largely lacking. We describe the development of a syllable stemmer for Tibetan. The stemmer is based on a set of rules that strive to identify the vowel, the core letter of the syllable, and then the other parts. We demonstrate the value of the stemmer with two applications: determining stem similarity of two syllables and word segmentation. Our stemmer is being made available as an open-source tool and word segmentation as a freely-available online tool.",
author = "Orna Almogi and Lena Dankin and Nachum Dershowitz and Yair Hoffman and Dimitri Pauls and Dorji Wangchuk and Lior Wolf",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG, part of Springer Nature 2018.; 17th International Conference on Intelligent Text Processing and Computational Linguistics, CICLing 2016 ; Conference date: 03-04-2016 Through 09-04-2016",
year = "2018",
doi = "https://doi.org/10.1007/978-3-319-75477-2_20",
language = "الإنجليزيّة",
isbn = "9783319754765",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "294--306",
editor = "Alexander Gelbukh",
booktitle = "Computational Linguistics and Intelligent Text Processing - 17th International Conference, CICLing 2016, Revised Selected Papers",
}