15 items

• 

  Development of Open Educational Resources (OER) for Natural Language Processing cite

  Cvetana Krstev, Biljana Lazić, Ranka Stanković, Giovanni Schiuma, Miladin Kotorčević (2015)

  In this paper we present the development of an online course at the edX BAEKTEL platform named “Lexical Recognition in the Natural Language Processing (NLP)”. It is based on the course of the same name for PhD studies at the University of Belgrade, Faculty of Philology. There are not many courses in Computational Linguistics (CL) on OER platforms, and there is none in Serbian either for CL or NLP. We have developed this course in order to improve this ...

  E-Learning, Open Educational Resources, Computational Linguistics, Lexical Resources, edX

  Cvetana Krstev, Biljana Lazić, Ranka Stanković, Giovanni Schiuma, Miladin Kotorčević. "Development of Open Educational Resources (OER) for Natural Language Processing" in The Sixth International Conference on e-Learning (eLearning-2015), September 2015, Belgrade, Serbia, Belgrade : Belgrade Metropolitan Univesity (2015)

• 

  E-Waste Management in Serbia, Focusing on the Possibility of Applying Automated Separation Using Robots cite

  Dragana Nišić, Branko Lukić, Zaviša Gordić, Uroš Pantelić, Arso Vukićević (2024)

  reciklaža, e-otpad, robot, separacija otpada, cirkularna ekonomija

  Dragana Nišić, Branko Lukić, Zaviša Gordić, Uroš Pantelić, Arso Vukićević. "E-Waste Management in Serbia, Focusing on the Possibility of Applying Automated Separation Using Robots" in Applied Sciences, MDPI AG (2024). https://doi.org/10.3390/app14135685

• 

  E-Connecting Balkan Languages cite

  Cvetana Krstev, Ranka Stanković, Duško Vitas, Svetla Koeva (2009)

  In this paper we present a versatile language processing tool that can be successfully used for many Balkan languages. This tool relies for its work on several sophisticated textual and lexical resources that were developed for most of Balkan languages. These resources are based on several de facto standards in natural language processing.

  Query expansion, e-dictionary, wordnet, proper name, aligned text

  Cvetana Krstev, Ranka Stanković, Duško Vitas, Svetla Koeva. "E-Connecting Balkan Languages" in Proceedings of the Workshop Workshop on Multilingual resources, technologies and evaluation for Central and Eastern European Languages, 17 September 2009, eds. C. Vertan, S. Piperidis, E. Paskaleva and Milena Slavcheva, Borovets, Bulgaria : Association for Computational Linguistics Stroudsburg, PA, USA (2009)

• 

  Machine learning based landslide assessment of the Belgrade metropolitan area: Pixel resolution effects and a cross-scaling concept cite

  Uroš Đurić, Miloš Marjanović, Zoran Radić, Biljana Abolmasov (2019)

  Improvements of Machine Learning-based landslide prediction models can be made by optimizing scale, customizing training samples to provide sets with the best examples, feature selection, etc. Herein, a novel approach, named Cross-Scaling, is proposed that includes the mixing of training and testing set resolutions. Hypothetically, training on a coarser resolution dataset and testing the model on a finer resolution should help the algorithm to better generalize ambiguous examples of landslide classes and yield fewer over/underestimations in the model. This ...

  klizišta, podložnost, mašinsko učenje

  Uroš Đurić, Miloš Marjanović, Zoran Radić, Biljana Abolmasov. " Machine learning based landslide assessment of the Belgrade metropolitan area: Pixel resolution effects and a cross-scaling concept" in Engineering Geology , Elsevier (2019). https://doi.org/10.1016/j.enggeo.2019.05.007

• 

  Osnove mašinskog učenja u hidrogeologiji cite

  Ivan Drakulić, Dušan Polomčić, Jelena Ratković (2024)

  Mašinsko učenje predstavlja skup metoda koje se u poslednje vreme koriste u brojnim naučnim oblastima i koje su uveliko promenile način na koji analiziramo podatke, pravimo predviđanja i rešavamo složene probleme. Poslednjih godina, mašinsko učenje se pokazalo kao moćan alat u svetu nauke, koji ima ogroman potencijal i u hidrogeologiji. Sa svojom sposobnošću da automatski uči iz ogromne količine podataka, mašinsko učenje otvara nove mogućnosti za rešavanje problema kao što su karakterizacija izdani, procena kvaliteta vode i predviđanje nivoa ...

  mašinsko učenje, hidrogeologija, podzemne vode

  Ivan Drakulić, Dušan Polomčić, Jelena Ratković. "Osnove mašinskog učenja u hidrogeologiji" in Zapisnici srpskog geološkog društva (za 2023. godinu), Srpsko geološko društvo (2024)

• 

  Sentiment Analysis of Serbian Old Novels cite

  Ranka Stanković, Miloš Košprdić, Milica Ikonić Nešić, Tijana Radović (2022)

  In this paper we present first study of Sentiment Analysis (SA) of Serbian novels from the 1840-1920 period. The preparation of sentiment lexicon was based on three existing lexicons: NRC, AFFIN and Bing with additional extensive corrections. The first phase of dataset refinement included filtering the word that are not found in Serbian morphological dictionary and in second automatic POS tagging and lemma were manually corrected. The polarity lexicon was extracted and transformed into ontolex-lemon and published as initial ...

  sentiment lexicon, sentiment analysis, distant-reading, machine learning, old novels

  Ranka Stanković, Miloš Košprdić, Milica Ikonić Nešić, Tijana Radović. "Sentiment Analysis of Serbian Old Novels" in Proceedings of the 2nd Workshop on Sentiment Analysis and Linguistic Linked Data, June 2022, Marseille, France, European Language Resources Association (2022)

• 

  Application of machine learning for diagnosing the operation of a deep well pump in oil production cite

  Maja Trikić (2024)

  This paper will thoroughly examine how machine learning can improve the diagnosis of deep well pumps by analyzing the role and function of the pumps, dynamograms, sensor technologies, and diagnostic methods.Our analysis will provide insights into modern techniques and approaches for enhancing the performance and reliability of oil production systems, targeting cost reduction and increased operational efficiency.

  deep well pump, dynamograms, machine learning, diagnostics of operating coditions,Random Forest, XGBoost

  Maja Trikić. Application of machine learning for diagnosing the operation of a deep well pump in oil production, 2024

• 

  Part of Speech Tagging for Serbian language using Natural Language Toolkit cite

  Ranka Stanković, Boro Milovanović (2020)

  Dok se razvijaju složeni algoritmi za NLP (obrada prirodnog jezika), osnovni zadaci kao što je označavanje ostaju veoma važni i još uvek izazovni. NLTK (Natural Language Toolkit) je moćna Python biblioteka za razvoj programa zasnovanih na NLP-u. Pokušavamo da iskoristimo ovu biblioteku za kreiranje PoS (vrsta reči) oznake za savremeni srpski jezik. Jedanaest različitih modela je kreirano korišćenjem NLTK API-ja za označavanje. Najbolji modeli se transformišu sa Brill tagerom da bi se poboljšala tačnost. Obučili smo modele na označenom ...

  obrada prirodnog jezika, mašinsko učenje, neuronske mreže

  Ranka Stanković, Boro Milovanović. "Part of Speech Tagging for Serbian language using Natural Language Toolkit" in 7th International Conference on Electrical, Electronic and Computing Engineering IcETRAN 2020, Academic Mind, Belgrade (2020)

• 

  Evaluating the deep learning software tools for large-scale enterprises using a novel TODIFFA-MCDM framework cite

  Zoran Gligorić, Ömer Faruk Görçün, Miloš Gligorić, Dragan Pamucar, Vladimir Simić, Hande Küçükönder (2024)

  duboko učenje, industrije velikih razmera, MAXC (maksimum kriterijuma), TODIFFA (totalni diferencijal alternative), izbor softvera za dubinsko učenje

  Zoran Gligorić, Ömer Faruk Görçün, Miloš Gligorić, Dragan Pamucar, Vladimir Simić, Hande Küçükönder. "Evaluating the deep learning software tools for large-scale enterprises using a novel TODIFFA-MCDM framework" in Journal of King Saud University - Computer and Information Sciences, Springer Science and Business Media LLC (2024). https://doi.org/10.1016/j.jksuci.2024.102079

• 

  Concepts for Improving Machine Learning Based Landslide Assessment cite

  Miloš Marjanović, Mileva Samardžić Petrović, Biljana Abolmasov, Uroš Đurić (2019)

  Katastar klizišta, Podložnost, Hazard, Mašinsko učenje, Uzorkovanje, Validacija

  Miloš Marjanović, Mileva Samardžić Petrović, Biljana Abolmasov, Uroš Đurić. "Concepts for Improving Machine Learning Based Landslide Assessment" in Natural Hazards GIS-based Spatial Modeling Using Data Mining Techniques, Advances in Natural and Technological Hazards Research, volume 48, Springer Nature Switzerland AG 2019 (2019). https://doi.org/10.1007/978-3-319-73383-8_2

• 

  Integrating landslide magnitude in the susceptibility assessment of the City of Doboj, using machine learning and heuristic approach cite

  Cvjetko Sandić, Miloš Marjanović, Biljana Abolmasov, Radislav Tošić (2023)

  In this work, landslide assessment of the Doboj City area was modeled by combining machine learning and heuristic tools. The machine learning part was used to map the Morphometric factor. i.e. probability of landslides based on relation between the magnitude of events and morphometric parameters: elevation, distance to streams, slope, profile curvature, and aspect. The Random Forest and Support Vector Machines algorithms were implemented in the learning protocol, which included several strategies: balancing of the training/testing set size, algorithm ...

  podložnost na kliženje, magnituda klizišta, mašinsko učenje, heuristički pristup, Doboj

  Cvjetko Sandić, Miloš Marjanović, Biljana Abolmasov, Radislav Tošić. "Integrating landslide magnitude in the susceptibility assessment of the City of Doboj, using machine learning and heuristic approach" in Journal of Maps, Taylor&Francis (2023). https://doi.org/ 10.1080/17445647.2022.2163199

• 

  Interpretation of Trace Element Chemistry of Zircons from Bor and Cukaru Peki: Conventional Approach and Random Forest Classification cite

  Dina Klimentyeva, Milos Velojic , Albrecht Von Quadt, Shawn Hood (2022)

  Geohemija cirkona, Mašinsko učenje, Timočki magmatski komplkes, Bor, Čukaru Peki

  Dina Klimentyeva, Milos Velojic , Albrecht Von Quadt, Shawn Hood. "Interpretation of Trace Element Chemistry of Zircons from Bor and Cukaru Peki: Conventional Approach and Random Forest Classification" in Geosciences (2022). https://doi.org/https://doi.org/10.3390/geosciences12110396

• 

  Sourcing of groundwater inflows into underground mining works based on statistical modelling and artificial neural networks – the “Čukaru Peki” Cu-Au mine case study cite

  Nebojša Atanacković, Jana Štrbački, Sunčica Gardijan, Vladimir Živanović (2024)

  rudničke vode, kvalitet podzemnih voda, rudnička hidrogeologija, statističko modeliranje, mašinsko učenje

  Nebojša Atanacković, Jana Štrbački, Sunčica Gardijan, Vladimir Živanović. "Sourcing of groundwater inflows into underground mining works based on statistical modelling and artificial neural networks – the “Čukaru Peki” Cu-Au mine case study" in IAH 2024 World Groundwater Congress - Interacting Groundwater, Davos, Švajcarska, 08-13.09.2024, Centre for Hydrogeology and Geothermics (CHYN), UNINE (2024)

• 

  Primena klasterizacije metodom K-srednjih vrednosti za ispitivanje hidrohemijskog diverziteta podzemnih voda na lokaciji Vrnjačke Banje cite

  Jana Štrbački, Vladimir Živanović, Nebojša Atanacković, Snežana Kretić (2024)

  Klasterizacija metodom k-srednjih vrednosti koristi se za razvrstavanje podataka u homogene grupe, tj. klastere, na osnovu odabranih varijabli i unapred zadatog broja klastera. Algoritam iterativnim postupkom određuje centre klastera i dodeljuje uzorke u klastere čijem su centru najbliži. Ovaj postupak pogodan je za raščlanjivanje i, samim tim, pojednostavljivanje obimnih skupova hidrohemijskih podataka, što je pokazano na primeru termo-mineralnih voda sa šireg područja Vrnjačke Banje. Pored same klasifikacije, opisana metoda pruža mogućnost provere hipoteza o strukturi podataka, npr. o postojanju ...

  multivarijantna statistička analiza, mašinsko učenje, termo-mineralne vode, Vrnjačka Banja

  Jana Štrbački, Vladimir Živanović, Nebojša Atanacković, Snežana Kretić. "Primena klasterizacije metodom K-srednjih vrednosti za ispitivanje hidrohemijskog diverziteta podzemnih voda na lokaciji Vrnjačke Banje" in XVII Srpski simpozijum o hidrogeologiji sa međunarodnim učešćem , Pirot, Srbija, 02-06. oktobar 2024, Beograd : Univerzitet u Beogradu - Rudarsko-geološki fakultet (2024). https://doi.org/10.5281/zenodo.13739553

• 

  SASA Dictionary as the Gold Standard for Good Dictionary Examples for Serbian cite

  Ranka Stanković, Branislava Šandrih, Rada Stijović, Cvetana Krstev, Duško Vitas, Aleksandra Marković (2019)

  У овом раду представљамо модел за избор добрих примера за речник српског језика и развој иницијалних компоненти модела. Метода која се користи заснива се на детаљној анализи различитих лексичких и синтактичких карактеристика у корпусу састављених од примера из пет дигитализованих свезака речника САНУ. Почетни скуп функција био је инспирисан сличним приступом и за друге језике. Дистрибуција карактеристика примера из овог корпуса упоређује се са карактеристиком дистрибуције узорака реченица ексцерпираних из корпуса који садрже различите текстове. Анализа је показала да ...

  Српски, добри примери из речника, аутоматизација израде речника, издвајање својстава, Машинско учење

  Ranka Stanković, Branislava Šandrih, Rada Stijović, Cvetana Krstev, Duško Vitas, Aleksandra Marković. "SASA Dictionary as the Gold Standard for Good Dictionary Examples for Serbian" in Electronic lexicography in the 21st century. Proceedings of the eLex 2019 conference , Lexical Computing CZ, s.r.o. (2019)