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CIKM
2011
Springer

Hybrid models for future event prediction

12 years 11 months ago
Hybrid models for future event prediction
We present a hybrid method to turn off-the-shelf information retrieval (IR) systems into future event predictors. Given a query, a time series model is trained on the publication dates of the retrieved documents to capture trends and periodicity of the associated events. The periodicity of historic data is used to estimate a probabilistic model to predict future bursts. Finally, a hybrid model is obtained by intertwining the probabilistic and the time-series model. Our empirical results on the New York Times corpus show that autocorrelation functions of time-series suffice to classify queries accurately and that our hybrid models lead to more accurate future event predictions than baseline competitors. Categories and Subject Descriptors H.3.0 [Information Storage and Retrieval]: General; H.3.1 [Information Storage and Retrieval]: Content Analysis and Indexing; H.3.3 [Information Storage and Retrieval]: Information Search and Retrieval General Terms Theory, Experimentation Keywords Fu...
Giuseppe Amodeo, Roi Blanco, Ulf Brefeld
Added 13 Dec 2011
Updated 13 Dec 2011
Type Journal
Year 2011
Where CIKM
Authors Giuseppe Amodeo, Roi Blanco, Ulf Brefeld
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