Seasonal Web Search Query Selection for Influenza-Like Illness (ILI) Estimation

Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt

Standard

Seasonal Web Search Query Selection for Influenza-Like Illness (ILI) Estimation. / Hansen, Niels Dalum; Mølbak, Kåre; Cox, Ingemar Johansson; Lioma, Christina.

SIGIR '17 Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval. Association for Computing Machinery, 2017. s. 1197-1200.

Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt

Harvard

Hansen, ND, Mølbak, K, Cox, IJ & Lioma, C 2017, Seasonal Web Search Query Selection for Influenza-Like Illness (ILI) Estimation. i SIGIR '17 Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval. Association for Computing Machinery, s. 1197-1200, 40th International ACM SIGIR Conference on Research and Development in Information Retrieval, Shinjuku, Tokyo, Japan, 07/08/2017. https://doi.org/10.1145/3077136.3080760

APA

Hansen, N. D., Mølbak, K., Cox, I. J., & Lioma, C. (2017). Seasonal Web Search Query Selection for Influenza-Like Illness (ILI) Estimation. I SIGIR '17 Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval (s. 1197-1200). Association for Computing Machinery. https://doi.org/10.1145/3077136.3080760

Vancouver

Hansen ND, Mølbak K, Cox IJ, Lioma C. Seasonal Web Search Query Selection for Influenza-Like Illness (ILI) Estimation. I SIGIR '17 Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval. Association for Computing Machinery. 2017. s. 1197-1200 https://doi.org/10.1145/3077136.3080760

Author

Hansen, Niels Dalum ; Mølbak, Kåre ; Cox, Ingemar Johansson ; Lioma, Christina. / Seasonal Web Search Query Selection for Influenza-Like Illness (ILI) Estimation. SIGIR '17 Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval. Association for Computing Machinery, 2017. s. 1197-1200

Bibtex

@inproceedings{3b66ce2e15c043858a3970dc19445cca,
title = "Seasonal Web Search Query Selection for Influenza-Like Illness (ILI) Estimation",
abstract = "Inuenza-like illness (ILI) estimation from web search data is an importantweb analytics task. The basic idea is to use the frequencies ofqueries in web search logs that are correlated with past ILI activityas features when estimating current ILI activity. It has been notedthat since inuenza is seasonal, this approach can lead to spuriouscorrelations with features/queries that also exhibit seasonality, buthave no relationship with ILI. Spurious correlations can, in turn, degradeperformance. To address this issue, we propose modeling theseasonal variation in ILI activity and selecting queries that are correlatedwith the residual of the seasonal model and the observed ILIsignal. Experimental results show that re-ranking queries obtainedby Google Correlate based on their correlation with the residualstrongly favours ILI-related queries.",
author = "Hansen, {Niels Dalum} and K{\aa}re M{\o}lbak and Cox, {Ingemar Johansson} and Christina Lioma",
year = "2017",
doi = "10.1145/3077136.3080760",
language = "English",
pages = "1197--1200",
booktitle = "SIGIR '17 Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval",
publisher = "Association for Computing Machinery",
note = "40th International ACM SIGIR Conference on Research and Development in Information Retrieval : SIGIR '17 ; Conference date: 07-08-2017 Through 11-08-2017",

}

RIS

TY - GEN

T1 - Seasonal Web Search Query Selection for Influenza-Like Illness (ILI) Estimation

AU - Hansen, Niels Dalum

AU - Mølbak, Kåre

AU - Cox, Ingemar Johansson

AU - Lioma, Christina

PY - 2017

Y1 - 2017

N2 - Inuenza-like illness (ILI) estimation from web search data is an importantweb analytics task. The basic idea is to use the frequencies ofqueries in web search logs that are correlated with past ILI activityas features when estimating current ILI activity. It has been notedthat since inuenza is seasonal, this approach can lead to spuriouscorrelations with features/queries that also exhibit seasonality, buthave no relationship with ILI. Spurious correlations can, in turn, degradeperformance. To address this issue, we propose modeling theseasonal variation in ILI activity and selecting queries that are correlatedwith the residual of the seasonal model and the observed ILIsignal. Experimental results show that re-ranking queries obtainedby Google Correlate based on their correlation with the residualstrongly favours ILI-related queries.

AB - Inuenza-like illness (ILI) estimation from web search data is an importantweb analytics task. The basic idea is to use the frequencies ofqueries in web search logs that are correlated with past ILI activityas features when estimating current ILI activity. It has been notedthat since inuenza is seasonal, this approach can lead to spuriouscorrelations with features/queries that also exhibit seasonality, buthave no relationship with ILI. Spurious correlations can, in turn, degradeperformance. To address this issue, we propose modeling theseasonal variation in ILI activity and selecting queries that are correlatedwith the residual of the seasonal model and the observed ILIsignal. Experimental results show that re-ranking queries obtainedby Google Correlate based on their correlation with the residualstrongly favours ILI-related queries.

U2 - 10.1145/3077136.3080760

DO - 10.1145/3077136.3080760

M3 - Article in proceedings

SP - 1197

EP - 1200

BT - SIGIR '17 Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval

PB - Association for Computing Machinery

T2 - 40th International ACM SIGIR Conference on Research and Development in Information Retrieval

Y2 - 7 August 2017 through 11 August 2017

ER -

ID: 195769168