prikaz prve stranice dokumenta Prepoznavanje imenovanih entiteta adresa
No public access
master's thesis
Prepoznavanje imenovanih entiteta adresa
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. urn:nbn:hr:168:736413
Čeović, Helena
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Čeović, H. (2021). Prepoznavanje imenovanih entiteta adresa (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:736413

Čeović, Helena. "Prepoznavanje imenovanih entiteta adresa." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. https://urn.nsk.hr/urn:nbn:hr:168:736413

Čeović, Helena. "Prepoznavanje imenovanih entiteta adresa." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. https://urn.nsk.hr/urn:nbn:hr:168:736413

Čeović, H. (2021). 'Prepoznavanje imenovanih entiteta adresa', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 21 June 2024, https://urn.nsk.hr/urn:nbn:hr:168:736413

Čeović H. Prepoznavanje imenovanih entiteta adresa [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2021 [cited 2024 June 21] Available at: https://urn.nsk.hr/urn:nbn:hr:168:736413

H. Čeović, "Prepoznavanje imenovanih entiteta adresa", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2021. Available at: https://urn.nsk.hr/urn:nbn:hr:168:736413

Metadata
TitlePrepoznavanje imenovanih entiteta adresa
Title (english)Named Entity Recognition for Addresses
AuthorHelena Čeović
MentorGoran Delač (mentor)
Committee memberGoran Delač (predsjednik povjerenstva)
Committee memberMarin Šilić (član povjerenstva)
Committee memberKlemo Vladimir (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2021-07-06, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Cilj ovog diplomskog rada je razvoj modela visoke točnosti za prepoznavanje imenovanih entiteta adresa. Izazovi uključuju raznolikost, dvosmislenost i kompleksnost entiteta adrese. Različite arhitekture modela korištene za treniranje klasifikatora su jednostavniji modeli logističke regresije i algoritam slučajnih šuma te složeniji model temeljen na dvosmjernoj povratnoj neuronskoj mreži s dodatnim slojem koji sadrži uvjetovana slučajna polja (BiLSTM-CRF) i implementiran je pomoću Flair knjižnice. Sva testiranja provedena su na dva skupa podataka koji se razlikuju po načinu označavanja temeljenom na granularnosti imenavanog entiteta: adresa kao cjelina i adresa sastavljena od podelemenata. Za oba skupa podataka najbolje rezultate postiže model temeljen na BiLSTM-CRF arhitekturi s jednim RNN slojem te treniran ili samo na BERT-u ili na kombinaciji BERT i GloVe embedding-a.
Abstract (english)
This thesis focuses on developing a high-performing named entity recognition model for addresses. Challenges including diversity, ambiguity and complexity of the address entity are introduced as well as the different model architectures used for training the classifier. These include the simpler logistic regression and random forest models as well as the more complex bidirectional LSTM network with a conditional random field layer (BiLSTM-CRF) implemented using Flair framework. Experiments are conducted using variously configured models on two sets of corpora tagged differently based on address entity granularity: entire address and address consisting of subparts. For both corpora, the best results are achieved on a BiLSTM-CRF architecture model with a single RNN layer trained on either standalone BERT embeddings or a stacked combination of BERT and GloVe.
Keywords
Keywords (english)
Languageenglish
URN:NBNurn:nbn:hr:168:736413
Study programmeTitle: Computing
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
Access conditionsClosed access
Terms of useLicence In copyright icon
Public note
Created on2023-01-13 12:01:06