Change search
CiteExportLink to record
Permanent link

Direct link
Cite
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
  • text
  • asciidoc
  • rtf
Datadrivet lärande av vägbeskrivningar
KTH, School of Computer Science and Communication (CSC).
KTH, School of Computer Science and Communication (CSC).
2013 (Swedish)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAlternative title
Data-driven learning of the meaning of route descriptions (English)
Abstract [sv]

Interaktionen mellan människor och datorer begränsas ofta av våra vitt skilda sätt att kommunicera på, exempelvis vid en beskrivning av en väg. I detta projekt försöker vi utveckla ett program som genom att analysera visuella och verbala vägbeskrivningar gjorda av mäniskor, kan gissa sig till ords betydelser genom att koppla ihop dem med fördefinierade objekt eller handlingar. Resultaten visar att det med en tillräcklig mängd data går att lära en dator ord som representerar specifika objekt eller rörelsemönster genom att hitta ord som sägs i samband rörelser i vissa riktningar eller i närheten av vissa objekt.

Abstract [en]

The interaction between humans and computers is often limited by the large differences of the ways we prefer to communicate, for example when trying to describe a route. In this project, we aim to develop a program that by analyzing visual and verbal human given route descriptions, can accurately guess the meaning of certain words by associating them with predefined objects or actions. The results indicate that with a sufficient amount of data, it is possible to learn the words representing certain objects or movement patterns by finding words said in conjunction with moving in certain directions or in the vicinity of certain objects.

Place, publisher, year, edition, pages
2013.
Series
Kandidatexjobb CSC, K13035
National Category
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-134952OAI: oai:DiVA.org:kth-134952DiVA: diva2:668862
Educational program
Master of Science in Engineering - Computer Science and Technology
Supervisors
Examiners
Available from: 2013-12-13 Created: 2013-12-02 Last updated: 2013-12-13Bibliographically approved

Open Access in DiVA

Datadrivet lärande av vägbeskrivningar(867 kB)16 downloads
File information
File name FULLTEXT01.pdfFile size 867 kBChecksum SHA-512
7454bca145b1d0b206b2b2023647776163e5e234ac37db29cc29dcdcde785e75da4e327bf5cb79e5e9f366bdc5c037689d31191ab755bd773fbdb11c38326189
Type fulltextMimetype application/pdf

Other links

http://www.csc.kth.se/utbildning/kth/kurser/DD143X/dkand13/Group6Gabriel/report/report_kristoffer_dmitrij.pdf
By organisation
School of Computer Science and Communication (CSC)
Computer Science

Search outside of DiVA

GoogleGoogle Scholar
Total: 16 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 76 hits
CiteExportLink to record
Permanent link

Direct link
Cite
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
  • text
  • asciidoc
  • rtf