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Hybrid Code Networks and its application
KTH, School of Electrical Engineering and Computer Science (EECS).
2018 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

Building a chatbot that fully understands human language is regarded as the hardest area in artificial intelligence. Despite of its progress, chatbots require further improvement. Hybrid Code Networks (HCNs), allows machines to keep track of conversations and allow more like a human-human conversation. In this paper, investigation on HCNs and its application on building a brief medical chatbot that allows examining pet’s potential illness is addressed.

Abstract [sv]

Att bygga en chatbot som fullständigt förstår människans språk anses vara det svåraste området inom artificiell intelligens. Trots framsteg kräver chatbots vidare utveckling. Hybridkodsnätverk (HCN) kan följa konversationer med människor och möjliggör ett mer mänskligt samtal mellan person och program. Denna avhandling undersöker HCN och dess tillämpning i en medicinsk chatbot med målet att diagnostisera potentiella sjukdomar för husdjur.

Place, publisher, year, edition, pages
2018.
Series
TRITA-EECS-EX ; 2018:520
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:kth:diva-240671OAI: oai:DiVA.org:kth-240671DiVA, id: diva2:1274706
Supervisors
Examiners
Available from: 2019-01-02 Created: 2019-01-02 Last updated: 2019-01-02Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
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  • vancouver
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  • de-DE
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  • sv-SE
  • Other locale
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Output format
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  • text
  • asciidoc
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