Thesis Details

Machine Comprehension Using Commonsense Knowledge

Bachelor's Thesis Student: Daniš Tomáš Academic Year: 2018/2019 Supervisor: Fajčík Martin, Ing.
Czech title
Strojové porozumění s použitím znalostní báze
Language
English
Abstract

In this thesis, the commonsense reasoning ability of modern neural systems is explored. The goal is to provide insight into the current state of research in this area and identify promising research directions. A state-of-the-art question-answering model has been implemented and experimented with in various scenarios. Unlike in older approaches, the model achieved comparable results with best available models for the target task without using any task-specific architecture. Furthermore, unintended statistical biases are discovered in a popular commonsense reasoning dataset which allow models to compute the correct answer even when it does not have sufficient information to do so. Based on these findings, recommendations and possible future research areas are suggested.

Keywords

neural network, commonsense reasoning, commonsense knowledge, machine learning, natural language processing, question answering, knowledge base

Department
Degree Programme
Information Technology
Files
Status
defended, grade B
Date
14 June 2019
Reviewer
Committee
Černocký Jan, prof. Dr. Ing. (DCGM FIT BUT), předseda
Hliněná Dana, doc. RNDr., Ph.D. (DMAT FEEC BUT), člen
Jaroš Jiří, doc. Ing., Ph.D. (DCSY FIT BUT), člen
Orság Filip, Ing., Ph.D. (DITS FIT BUT), člen
Rychlý Marek, RNDr., Ph.D. (DIFS FIT BUT), člen
Citation
DANIŠ, Tomáš. Machine Comprehension Using Commonsense Knowledge. Brno, 2019. Bachelor's Thesis. Brno University of Technology, Faculty of Information Technology. 2019-06-14. Supervised by Fajčík Martin. Available from: https://www.fit.vut.cz/study/thesis/21703/
BibTeX
@bachelorsthesis{FITBT21703,
    author = "Tom\'{a}\v{s} Dani\v{s}",
    type = "Bachelor's thesis",
    title = "Machine Comprehension Using Commonsense Knowledge",
    school = "Brno University of Technology, Faculty of Information Technology",
    year = 2019,
    location = "Brno, CZ",
    language = "english",
    url = "https://www.fit.vut.cz/study/thesis/21703/"
}
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