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Deterministic and Flexible Parallel Latent Feature Models Learning Framework for Probabilistic Knowledge Graph
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Systems and Technology.
2018 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Knowledge Graph is a rising topic in the field of Artificial Intelligence. As the current trend of knowledge representation, Knowledge graph research is utilizing the large knowledge base freely available on the internet.

Knowledge graph also allows inspection, analysis, the reasoning of all knowledge in reality. To enable the ambitious idea of modeling the knowledge of the world, different theory and implementation emerges. Nowadays, we have the opportunity to use freely available information from Wikipedia and Wikidata. The thesis investigates and formulates a theory about learning from Knowledge Graph. The thesis researches probabilistic knowledge graph. It only focuses on a branch called latent feature models in learning probabilistic knowledge graph. These models aim to predict possible relationships of connected entities and relations. There are many models for such a task. The metrics and training process is detailed described and improved in the thesis work. The efficiency and correctness enable us to build a more complex model with confidence. The thesis also covers possible problems in finding and proposes future work.

Place, publisher, year, edition, pages
2018. , p. 59
Keywords [en]
Text classification, Recurrent neural network, Convolutional neural network
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:miun:diva-35788Local ID: DT-V18-A2-002OAI: oai:DiVA.org:miun-35788DiVA, id: diva2:1296264
Subject / course
Computer Engineering DT1
Supervisors
Examiners
Available from: 2019-03-14 Created: 2019-03-14 Last updated: 2019-03-14Bibliographically approved

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf