From post

Modeling OOV Words With Letter N-Grams in Statistical Taggers: Preliminary Work in Biomedical Entity Recognition.

, и . NODALIDA, том 85 из Linköping Electronic Conference Proceedings, стр. 181-193. Linköping University Electronic Press, (2013)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed.

No persons found for author name Silfverberg, Miikka
add a person with the name Silfverberg, Miikka
 

Другие публикации лиц с тем же именем

Using HFST - Helsinki Finite-State Technology for Recognizing Semantic Frames., , , и . SFCM, том 537 из Communications in Computer and Information Science, стр. 124-136. Springer, (2015)Kernel Density Estimation for Text-Based Geolocation., , и . AAAI, стр. 145-150. AAAI Press, (2015)SIGMORPHON 2020 Shared Task 0: Typologically Diverse Morphological Inflection., , , , , , , , , и 18 other автор(ы). SIGMORPHON, стр. 1-39. Association for Computational Linguistics, (2020)Multiple Sources are Better Than One: Incorporating External Knowledge in Low-Resource Glossing., , и . CoRR, (2024)Resisting the Lure of the Skyline: Grounding Practices in Active Learning for Morphological Inflection., , , и . ACL (Short Papers), стр. 47-55. Association for Computational Linguistics, (2024)HFST—Framework for Compiling and Applying Morphologies, , , , и . том Vol. 100 из Communications in Computer and Information Science, стр. 67-85. (2011)Modeling OOV Words With Letter N-Grams in Statistical Taggers: Preliminary Work in Biomedical Entity Recognition., и . NODALIDA, том 85 из Linköping Electronic Conference Proceedings, стр. 181-193. Linköping University Electronic Press, (2013)Predictive Text Entry for Agglutinative Languages Using Unsupervised Morphological Segmentation., , и . CICLing (2), том 7182 из Lecture Notes in Computer Science, стр. 478-489. Springer, (2012)Embedded Translations for Low-resource Automated Glossing., , и . CoRR, (2024)Accelerated Estimation of Conditional Random Fields using a Pseudo-Likelihood-inspired Perceptron Variant., , , и . EACL, стр. 74-78. The Association for Computer Linguistics, (2014)