Scalability of Semantic Analysis in Natural Language Processing – RNDr. Radim Řehůřek, Ph.D.
RNDr. Radim Řehůřek, Ph.D.
Doctoral thesis
Scalability of Semantic Analysis in Natural Language Processing
Scalability of Semantic Analysis in Natural Language Processing
Abstract:
Práce se zabývá dolováním dat z rozsáhlých korpusů. Zaměřuje se na robustní statistické metody, které dokáží automatizovaně vytvořit kompaktní sémantickou reprezentaci volného textu, tj. bez použití metadat či ručního vstupu člověka. První část práce se zabývá škálovatelností metod Latent Semantic Analysis (LSA) a Latent Dirichlet Allocation (LDA). Představuji nové algoritmy pro škálovatelnou tvorbu …moreAbstract:
Data mining applications that work over input of very large scale (web-scale problems) pose challenges that are new and exciting both academically and commercially. Any web-scale algorithm must be robust (dealing gracefully with the inevitable data noise), scalable (capable of efficiently processing large input) and reasonably automated (as human intervention is very costly and often impossible on …more
Language used: English
Date on which the thesis was submitted / produced: 19. 8. 2011
Identifier:
https://is.muni.cz/th/p5hkr/
Thesis defence
- Date of defence: 12. 9. 2011
- Supervisor: prof. PhDr. Karel Pala, CSc.
- Reader: Dr. Johannes Leveling, Dr. Martin Rajman
Citation record
Full text of thesis
Contents of on-line thesis archive
Published in Theses:- světu
Other ways of accessing the text
Institution archiving the thesis and making it accessible: Masarykova univerzita, Fakulta informatikyMasaryk University
Faculty of InformaticsDoctoral programme / field:
Informatics (4-years) / Informatics
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