Ensemble learned vaccination uptake prediction using web search queries

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

We present a method that uses ensemble learning to combine clinical and web-mined time-series data in order to predict future vaccination uptake. The clinical data is official vaccination registries, and the web data is query frequencies collected from Google Trends. Experiments with official vaccine records show that our method predicts vaccination uptake eff?ectively (4.7 Root Mean Squared Error). Whereas performance is best when combining clinical and web data, using solely web data yields comparative performance. To our knowledge, this is the ?first study to predict vaccination uptake using web data (with and without clinical data).
OriginalsprogEngelsk
TitelProceedings of the 25th ACM International Conference on Information and Knowledge Management
Antal sider4
ForlagIEEE
Publikationsdato2016
Sider1953-1956
ISBN (Elektronisk)978-1-4503-4073-1
DOI
StatusUdgivet - 2016
Begivenhed25th ACM International Conference on Information and Knowledge Management - Indianapolis, USA
Varighed: 24 okt. 201628 okt. 2016
Konferencens nummer: 25

Konference

Konference25th ACM International Conference on Information and Knowledge Management
Nummer25
LandUSA
ByIndianapolis
Periode24/10/201628/10/2016

    Forskningsområder

  • cs.IR, stat.AP

ID: 167516168