miun.sePublications
Change search
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
Anpassning av mobilnotifikationer med hjälp av maskininlärning
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Systems and Technology.
2019 (Swedish)Independent thesis Basic level (professional degree), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

The aim of this study has been to answer the question whether it is possible to obtain notifications that work with the user, instead of against, which can be experienced as stressful and bothersome. To decrease the stressful notifications an application was created which acted as a notification control. The application used machine learning to predict when the user wanted to receive their notifications. For an artificial intelligence to work there needs to be a pattern recognition. In this case the pattern recognition that was used is called the association rule analysis. The association rule analysis used a tree called fp-growth. After the application was made, a usability test was made before and after the installation of the application. The usability test was testing if the user experienced stress and how the application worked. The study showed that screen time decreased by one hour and the number of times the mobile was opened was also reduced. This survey requires more data as it may be that the user was not affected by the application but only randomly used the mobile phone less.

Abstract [sv]

Denna studie handlade om att försöka minska störande notifikationer som kan upplevas som stressande och irriterande. Det som skapades var en applikation som agerade som en notifikationskontroll. Denna applikation fungerar med hjälp av maskininlärning som ska förutse när användaren ville ta emot sina notifikationer. Den mönsterigenkännande artificiella intelligensen som användes kallas associationsregelanalys. Associationsregelanalysen använde sig av ett träd som kallas fp-growth. Det gjordes ett användartest före installation av applikationen och ett användartest efter för att se hur användaren upplevde stress men även själva applikationen. Studien visade att skärmtiden minskade med en timme och antalet gånger som mobilen öppnades minskades också. Denna undersökning kräver mer data då det kan vara så att användaren inte blev påverkad av applikationen utan endast slumpmässigt använde mobiltelefonen mindre.

Place, publisher, year, edition, pages
2019. , p. 31
Keywords [en]
Human-mobile-interaction, Java, machine learning, AI
National Category
Software Engineering
Identifiers
URN: urn:nbn:se:miun:diva-36451Local ID: DT-V19-G3-016OAI: oai:DiVA.org:miun-36451DiVA, id: diva2:1330034
Subject / course
Computer Engineering DT1
Educational program
Master of Science in Engineering - Computer Engineering TDTEA 300 higher education credits
Supervisors
Examiners
Available from: 2019-06-25 Created: 2019-06-25 Last updated: 2019-06-25Bibliographically approved

Open Access in DiVA

fulltext(789 kB)10 downloads
File information
File name FULLTEXT01.pdfFile size 789 kBChecksum SHA-512
c9a95efa2609d5b6d86a78faf8ba35f729fdca080a0dccce02ee61d55e6b2ce87aaa30f9a61f55aabfb7fceb350079d5b2b70a8cf86406d692e431c999af44c6
Type fulltextMimetype application/pdf

Search in DiVA

By author/editor
Saveh, Diana
By organisation
Department of Information Systems and Technology
Software Engineering

Search outside of DiVA

GoogleGoogle Scholar
Total: 10 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: 14 hits
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