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Chatbots and natural automatedlanguage: A comparison between rst word and most signicantword search
KTH, School of Computer Science and Communication (CSC).
KTH, School of Computer Science and Communication (CSC).
2014 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

This study aims to determine if there is any dierence in the perceived naturalness of chatbots implemented with either a rst word search- or a most signicant word search-algorithm. To this end two versions of the same chatbot were implemented using parsed movie dialogue used as a knowledge base and evaluated using methods developed for chatbot competitions. The results of the study were inconclusive and no statistically certain dierence between the two implementations was found.

Place, publisher, year, edition, pages
2014.
National Category
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-157680OAI: oai:DiVA.org:kth-157680DiVA: diva2:771048
Examiners
Available from: 2014-12-12 Created: 2014-12-12 Last updated: 2014-12-12Bibliographically approved

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fulltext(232 kB)360 downloads
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File name FULLTEXT01.pdfFile size 232 kBChecksum SHA-512
eeb4971419b90149cc36c6090cfcd0de59db76d40510cbb051eaa7da3f78c53fc0aedf6953c6bd337f749c037fbf2b41d3cec1325bf11078bf8a1f041617a2fd
Type fulltextMimetype application/pdf

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Computer Science

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • 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
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