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Showing results 1 to 10 of 10
Issue DateTitleInvolved Person(s)
2017A Twitter corpus and benchmark resources for german sentiment analysisCieliebak, Mark; Deriu, Jan Milan; Egger, Dominic; Uzdilli, Fatih
2016Adverse drug reaction detection using an adapted sentiment classifierUzdilli, Fatih; Cieliebak, Mark; Egger, Dominic
2015Back to the Future : Time-Travelling-Debugger als Alternative zu klassischen DebuggernSchutzbach, Daniel; Uzdilli, Fatih; Cieliebak, Mark
2014JOINT_FORCES : unite competing sentiment classifiers with random forestDürr, Oliver; Uzdilli, Fatih; Cieliebak, Mark
2014Meta-classifiers easily improve commercial sentiment detection toolsCieliebak, Mark; Dürr, Oliver; Uzdilli, Fatih
2015PANOPTES : automated article segmentation of newspaper pages for "Real Time Print Media Monitoring“Arnold, Marek; Cieliebak, Mark; Stadelmann, Thilo; Stampfli, Jan; Uzdilli, Fatih
2013Potential and limitations of commercial sentiment detection toolsCieliebak, Mark; Dürr, Oliver; Uzdilli, Fatih
2015Swiss-Chocolate : combining flipout regularization and random forests with artificially built subsystems to boost text-classification for sentimentUzdilli, Fatih; Jaggi, Martin; Egger, Dominic; Julmy, Pascal; Derczynski, Leon, et al
2014Swiss-chocolate : sentiment detection using sparse SVMs and part-of-speech n-gramsJaggi, Martin; Uzdilli, Fatih; Cieliebak, Mark
2016Twitter can help to find adverse drug reactionsCieliebak, Mark; Egger, Dominic; Uzdilli, Fatih