Intrinzično otkrivanje plagijata u studentskim radovima

undergraduate thesis

• Title (english): Intrinsic Plagiarism Detection in Student Theses
• Author: David Lozić
• Mentor: Jan Šnajder (mentor)
• Committee member: Jan Šnajder (član povjerenstva)
• Committee member: Domagoj Alagić (član povjerenstva)
• Committee member: Martin Tutek (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; Zagreb
• Defense date and country: 2017-09-11, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Computing

Abstract

Cilj intrinzičnog otkrivanja plagijata je prepoznavanje krađe unutar dokumenta bez pomoći referentnih tekstova. U ovom radu su predložena dva pristupa. Prvi koristi one-class SVM u prepoznavanju stršećih vrijednosti, dok drugi radi klasifikaciju koristeći niz klasifikatora. Za potrebe zadatka stvoren je umjetni skup podataka gdje su dokumenti analizirani na razini rečenice koristeći tehniku klizećeg prozora. Iako su postignuti pozitivni rezultati, sustav nije dovoljno učinkovit za samostalnu detekciju plagijata. F1 rezultat prvog modela je 0.3, dok je F1 rezultat drugog modela 0.25 za klasu plagijata.

Abstract (english)

The goal of intrinsic plagiarism detection is to uncover theft without the aid of external references by analyzing the discrepancies within a single corpus. In this thesis, two approaches are proposed. One focuses one outlier detection using the one-class SVM, and the other performs classification using several classifiers. An artificial dataset was created for the task and the documents are analyzed on a sentence level using a sliding window. While there have been some positive results, the system alone is not satisfactory enough for confident plagiarism detection on the sentence level. The first model scored an F1 score of 0.3 on the plagiarism class and the second model achieved an F1 score of 0.25.

• Keywords: obrada prirodnog jezika; strojno u učenje; detekcija plagijata; intrinzična detekcija plagijata; hrvatski jezik; SVM; one-class SVM
• Keywords (english): Natural language processing; machine learning; plagiarism detection; intrinsic plagiarism detection; Croatian language; SVM; one-class SVM
• Language: english
• URN:NBN: urn:nbn:hr:168:133594
• Study programme: Title: Computing; Study programme type: university; Study level: undergraduate; Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Closed access
• Created on: 2019-03-13 22:22:57