Izgradnja aplikacije za pretprocesiranje teksta

master's thesis

• Title (english): Building a text preprocessing application
• Author: Anela Rački
• Mentor: Ivan Dunđer (mentor)
• Committee member: Sanja Seljan (član povjerenstva)
• Committee member: Vjera Lopina (član povjerenstva)
• Committee member: Ivan Dunđer (član povjerenstva)
• Granter: University of Zagreb; Faculty of Humanities and Social Sciences; (Department of information and Communication sciences); Zagreb
• Defense date and country: 2024-06-27, Croatia
• Scientific / art field, discipline and subdiscipline: SOCIAL SCIENCES; Information and Communication Sciences

Abstract

Pretprocesiranje teksta važna je tehnika koja se koristi za čišćenje i transformiranje nestrukturiranih tekstualnih podatka i njihovu pripremu za daljnju analizu. Standardni postupak pretprocesiranja teksta uključuje uklanjanje interpunkcije, transformiranje velikih u mala slova, uklanjanje stop riječi i HTML oznaka, korjenovanje, tokenizaciju i lematizaciju. Cilj ovog diplomskog rada je izgradnja aplikacije koja će skratiti proces pretprocesiranja teksta i omogućiti njenim korisnicima bolji fokus na istraživanje i obradu prirodnog jezika. Rad se sastoji od teorijskog i praktičnog djela. Teorijski dio fokusiran je na važnost pretprocesiranja teksta i tehnike korištene za pretprocesiranje. U praktičnom djelu prikazana je metodologija izgradnje aplikacije u programskom jeziku Python. Zaključno je provedeno testiranje i evaluacija aplikacije.

Abstract (english)

Text preprocessing is an important technique used to clean and transform unstructured text data and prepare it for further analysis. Standard text preprocessing includes punctuation removal, lowercasing, removing stop words and HTML tags, stemming, tokenization, and lemmatization. The goal of this master thesis is to build an application that will shorten the text preprocessing process and enable its users to focus on natural language research and processing. The thesis consists of a theoretical and a practical part. The theoretical part is focused on the importance of text preprocessing and the techniques used for preprocessing. The practical part consists of presenting the methodology of building the application in the Python programming language. Finally, testing and evaluation of the application was carried out.

• Keywords: pretprocesiranje teksta; čišćenje nestrukturiranih podataka; obrada prirodnog jezika; Python programiranje
• Keywords (english): text preprocessing; unstructured data cleaning; natural language processing; Python programming
• Language: croatian
• URN:NBN: urn:nbn:hr:131:732915
• Study programme: Title: Information Sciences; specializations in: Informatology, Information Sciences (teaching), Information Sciences (research); Course: Information Sciences (research); Study programme type: university; Study level: graduate; Academic / professional title: magistar/magistra informacijskih znanosti (magistar/magistra informacijskih znanosti)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Open access
• Created on: 2024-07-03 18:09:50