Загрузка...
Complex temporal topic evolution modelling using the Kullback-Leibler divergence and the Bhattacharyya distance
The rapidly expanding corpus of medical research literature presents major challenges in the understanding of previous work, the extraction of maximum information from collected data, and the identification of promising research directions. We present a case for the use of advanced machine learning...
Сохранить в:
| Опубликовано в: : | EURASIP J Bioinform Syst Biol |
|---|---|
| Главные авторы: | , |
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
Springer International Publishing
2016
|
| Предметы: | |
| Online-ссылка: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5042987/ https://ncbi.nlm.nih.gov/pubmed/27746813 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s13637-016-0050-0 |
| Метки: |
Добавить метку
Нет меток, Требуется 1-ая метка записи!
|