prikaz prve stranice dokumenta Numerical and machine learning methods in automatic text summarization
  Download
PDF 529.49 KB
master's thesis
Numerical and machine learning methods in automatic text summarization
2022. urn:nbn:hr:166:511169
Sokol, Domina
University of Split
Faculty of Science
Department of Mathematics

Cite this document

Sokol, D. (2022). Numerical and machine learning methods in automatic text summarization (Master's thesis). Split: University of Split, Faculty of Science. Retrieved from https://urn.nsk.hr/urn:nbn:hr:166:511169

Sokol, Domina. "Numerical and machine learning methods in automatic text summarization." Master's thesis, University of Split, Faculty of Science, 2022. https://urn.nsk.hr/urn:nbn:hr:166:511169

Sokol, Domina. "Numerical and machine learning methods in automatic text summarization." Master's thesis, University of Split, Faculty of Science, 2022. https://urn.nsk.hr/urn:nbn:hr:166:511169

Sokol, D. (2022). 'Numerical and machine learning methods in automatic text summarization', Master's thesis, University of Split, Faculty of Science, accessed 12 December 2024, https://urn.nsk.hr/urn:nbn:hr:166:511169

Sokol D. Numerical and machine learning methods in automatic text summarization [Master's thesis]. Split: University of Split, Faculty of Science; 2022 [cited 2024 December 12] Available at: https://urn.nsk.hr/urn:nbn:hr:166:511169

D. Sokol, "Numerical and machine learning methods in automatic text summarization", Master's thesis, University of Split, Faculty of Science, Split, 2022. Available at: https://urn.nsk.hr/urn:nbn:hr:166:511169

Please login to the repository to save this object to your list.
Metadata
TitleNumerical and machine learning methods in automatic text summarization
Title (croatian)Numeričke metode i strojno učenje u automatskom skraćivanju teksta
AuthorDomina Sokol
MentorSaša Mladenović (mentor)
Committee memberSaša Mladenović (predsjednik povjerenstva)
Committee memberMilica Klaričić Bakula (član povjerenstva)
Committee memberStipe Marić (član povjerenstva)
GranterUniversity of Split
Faculty of Science
(Department of Mathematics)
Split
Defense date and country2022-09-23, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Scientific / art field,
discipline and subdiscipline		NATURAL SCIENCES
Mathematics
Abstract
Text summarization is a task in natural language processing with the goal of producing meaningful summaries from given text, by the use of a computer. There are two main approaches to this task: numerical methods for extractive summarizing, and machine learning methods for extractive and abstractive summarizing. The objective of this master’s thesis is to provide an overview of both of these methods, present their theoretical background and intuition, give a historical context for them, and show practical usage on examples.
Abstract (croatian)
Skraćivanje teksta je zadatak obrade prirodnog jezika s ciljem stvaranja smislenih sažetaka zadanog teksta uz pomoć računala. Postoje dva glavna pristupa ovome zadatku: numeričke metode za ekstraktivno sažimanje i metode strojnog učenja za ekstraktivno i apstraktivno sažimanje. Cilj ovog diplomskog rada je dati osvrt na obje ove metode, predstaviti njihovu teorijsku pozadinu i intuiciju, dati povijesni kontekst za njih te pokazati praktično korištenje na primjerima.
Keywords
Keywords (croatian)
Languageenglish
URN:NBNurn:nbn:hr:166:511169
Study programmeTitle: Mathematics; specializations in: major in pure mathematics, major in computing, major in teaching, major in statistics and computing
Course: major in computing
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra matematike (magistar/magistra matematike)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2022-12-19 12:27:33