Generation of Test Questions from RDF Files Using PYTHON']PYTHON and SPARQL

被引：5
|
作者：
Omarbekova, Assel [1 ]
Sharipbay, Altynbek [1 ]
Barlybaev, Alibek [1 ]
机构：
[1] LN Gumilyov Eurasian Natl Univ, Fac Informat Technol, Astana, Kazakhstan
来源：
2017 INTERNATIONAL CONFERENCE ON CONTROL ENGINEERING AND ARTIFICIAL INTELLIGENCE (CCEAI 2017) | 2017年 / 806卷
关键词：
D O I：
10.1088/1742-6596/806/1/012009
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This article describes the development of the system for the automatic generation of test questions based on the knowledge base. This work has an applicable nature and provides detailed examples of the development of ontology and implementation the SPARQL queries in RDF-documents. Also it describes implementation of the program generating questions in the Python programming language including the necessary libraries while working with RDF-files.
引用
收藏
页数：6
相关论文
共 50 条
  • [41] Predicting Type Annotations for Python']Python using Embeddings from Graph Neural Networks
    Ivanov, Vladimir
    Romanov, Vitaly
    Succi, Giancarlo
    PROCEEDINGS OF THE 23RD INTERNATIONAL CONFERENCE ON ENTERPRISE INFORMATION SYSTEMS (ICEIS 2021), VOL 1, 2021, : 548 - +
  • [42] Generating Python']Python Mutants From Bug Fixes Using Neural Machine Translation
    Asik, Sergen
    Yayan, Ugur
    IEEE ACCESS, 2023, 11 : 85678 - 85693
  • [43] viskillz-blender-A Python']Python package to generate assets of Mental Cutting Test exercises using Blender
    Toth, Robert
    Toth, Balint
    Hoffmann, Miklos
    Zichar, Marianna
    SOFTWAREX, 2023, 22
  • [44] Experiences Using a Novel Python']Python-Based Hardware Modeling Framework for Computer Architecture Test Chips
    Torng, Christopher
    Wang, Moyang
    Sudheendra, Bharath
    Murali, Nagaraj
    Jayasuriya, Suren
    Srinath, Shreesha
    Pritchard, Taylor
    Ying, Robin
    Batten, Christopher
    2016 IEEE HOT CHIPS 28 SYMPOSIUM (HCS), 2016,
  • [45] Creation of time series models based on deep learning for generation of probabilistic forecasts using GluonTS and Python']Python
    Cancino-Villatoro, Karina
    Solis, Alfredo Castillo
    Castillo-Estrada, Christian
    Juarez-Ramirez, Reyes
    2023 11TH INTERNATIONAL CONFERENCE IN SOFTWARE ENGINEERING RESEARCH AND INNOVATION, CONISOFT 2023, 2023, : 265 - 274
  • [46] Cloud segmentation property extraction from total sky image repositories using Python']Python
    Igoe, Damien P.
    Parisi, Alfio, V
    Downs, Nathan J.
    INSTRUMENTATION SCIENCE & TECHNOLOGY, 2019, 47 (05) : 522 - 534
  • [47] PDB2DAT: Automating LAMMPS data file generation from PDB molecular systems using Python']Python, Rdkit, and Pysimm
    Assaf, Eli I.
    Liu, Xueyan
    Lin, Peng
    Erkens, Sandra
    SOFTWARE IMPACTS, 2024, 20
  • [48] Automated and meta-structure solution from powder diffraction in Python']Python using pyobjcryst
    Favre-Nicolin, V.
    ACTA CRYSTALLOGRAPHICA A-FOUNDATION AND ADVANCES, 2022, 78 : E269 - E269
  • [49] Towards an automatic SPARQL query generation from ontology competency questions
    Benhocine K.
    Hansali A.
    Zemmouchi-Ghomari L.
    Ghomari A.R.
    International Journal of Computers and Applications, 2022, 44 (10) : 971 - 980
  • [50] Generating Training Data Using Python']Python Scripts for Automatic Extraction of Landmarks from Tooth Models
    Kato, Akiko
    Hori, Miki
    Hori, Tadasuke
    Jincho, Makoto
    Sekine, Hironao
    Kawai, Tatsushi
    JOURNAL OF HARD TISSUE BIOLOGY, 2022, 31 (02) : 95 - 100
12345