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Упит dcterms_subject_txt:E-Learning

10 items

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

    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
    ... biblioteka Srbije: Belgrade. p. 117-122. [10] Stanković, R., et al., Building terminological resources in an e-learning environment, in The third International Conference on e-Learning. Belgrade, Serbia. p. 114-119. [11] Paumier, S., Unitex 3.1 Beta: User Manual. 2015, Paris: Université Paris-Est ...
    ... Filološki fakultet: Beograd. [15] Radojičić, M., et al., Creating an environment for free education and technology enhanced learning, in The Fifth International Conference on e-Learning (eLearning-2014). 2014: Belgrade, Serbia. p. 44-47. ...
    ... Language Processing | Cvetana Krstev, Biljana Lazić, Ranka Stanković, Giovanni Schiuma, Miladin Kotorčević | The Sixth International Conference on e-Learning (eLearning- 2015), September 2015, Belgrade, Serbia | 2015 | | http://dr.rgf.bg.ac.rs/s/repo/item/0001756 Дигитални репозиторијум Рударско-геолошког ...

  • E-Connecting Balkan Languages

    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
    ... Измењено: 2023-10-14 03:28:46 E-Connecting Balkan Languages Cvetana Krstev, Ranka Stanković, Duško Vitas, Svetla Koeva Дигитални репозиторијум Рударско-геолошког факултета Универзитета у Београду [ДР РГФ] E-Connecting Balkan Languages | Cvetana Krstev, Ranka Stanković ...
    ... 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 | 2009 | | http://dr.rgf.bg.ac.rs/s/repo/item/0001597 Дигитални репозиторијум Рударско-геолошког факултета Универзитета ...
    ... archives faculty publications available in open access, as well as the employees' publications. - The Repository is available at: www.dr.rgf.bg.ac.rs E-Connecting Balkan Languages Cvetana Krstev Faculty of Philology University of Belgrade cvetana@matf.bg.ac.rs Ranka Stanković Faculty of Mining ...

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

    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

  • Sentiment Analysis of Serbian Old Novels

    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

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

    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
    ... SENSOR FAULTS USING MACHINE LEARNING IN SUBMERSIBLE PUMPING ........a e 41 6.1 Sensor fault diagnostics.... 6.2. Condition diagnostics ... 6.3. Application of methods and materials.......aaaaaaaaaaa a naaaanaaaaaaaoi 45 6.3.1. Fundamentals of machine learning........aaaaaa a anaaaaaaaaoi 45 ...
    ... []] i e e -25 F3 “ bj Low pass H igh pass |, 2 P . o Low pass High pass Figure 6.7. Application of DWT to a normalized dynamometric chart from a well. Equations (10) and (13) were used along with discrete values for (s) and (b) 6.4. Methodology The application of machine learning to c ...
    ... to the implementation of the model. O Š' U l—E e > @ –> eee > Problem Get the data L L, Algorithm selection observation Model validation Data exploration Data preparation Figure 6.8 illustrates the steps of experimentation in machine learning that were used in this study. In the problem ...

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

    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
    ... USA, 2000 [22] E. Brill, “A simple rule-based part of speech tagger”, Proc. Third conference on Applied natural language processing (ANLC '92), Stroudsburg, Pennsylvania, USA, Mar. 1992. [23] R. Stanković, B. Šandrih, C. Krstev, M. Utvić, and M. Škorić, “Machine Learning and Deep Neural Net ...
    ... demonstrated with the Perceptron tagger: 92,52 – 95,76% accuracy for the different tagsets. Index Terms—Natural Language Processing; Machine Learning; Neural Network. I. INTRODUCTION In the last couple of years, a big advancement in the field of Natural Language Processing has occurred ...
    ... in this research is achieved with the Perceptron tagger, a neural network which is more than a decade old. Since then, a breakthrough with deep learning has happened, so there’s a strong belief that further improvements can be made with the latest neural network models [24]. However, there is a ...

  • Concepts for Improving Machine Learning Based Landslide Assessment

    Miloš Marjanović, Mileva Samardžić Petrović, Biljana Abolmasov, Uroš Đurić (2019)
    Katastar klizišta, Podložnost, Hazard, Mašinsko učenje, Uzorkovanje, Validacija

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

    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

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

    Dina Klimentyeva, Milos Velojic , Albrecht Von Quadt, Shawn Hood (2022)
    Geohemija cirkona, Mašinsko učenje, Timočki magmatski komplkes, Bor, Čukaru Peki

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

    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
    ... Oxford University Press. Bird, S., Loper, E. & Klein E. (2009). Natural Language Processing with Python. O’Reilly Media Inc. Eibe, F., Hall, M. A. & Witten, I. (2016). The Weka Workbench. Online Appendix for "Data Mining: Practical Machine Learning Tools and Techniques". Morgan Kaufmann, Fourth ...
    ... candidate examples, represented as feature- vectors, are used with the GDEX ranking tool for Serbian candidate examples and a supervised machine learning model for classification on standard and non-standard Serbian sentences, for further integration into a solution for present and future dictionary ...
    ... dictionary production projects. Keywords: Serbian; good dictionary examples; automatization of dictionary-making; feature extraction; machine learning 1. Introduction 1.1 The aim of the paper This paper outlines an approach to providing support for building different kinds of monolingual descriptive ...