000197180 001__ 197180
000197180 005__ 20190316235845.0
000197180 037__ $$aCONF
000197180 245__ $$aA Novel Human Computation Game for Critique Aggregation
000197180 269__ $$a2013
000197180 260__ $$c2013
000197180 336__ $$aConference Papers
000197180 520__ $$aWe present a human computation game based on the popular board game - Dixit. We ask the players not only for annotations, but for a direct critique of the result of an automated system.We present the results of the initial run of the game, in which the answers of 15 players were used to profile the mistakes of an aspect-based opinion mining system. We show that the gameplay allowed us to identify the major faults of the extracted opinions. The players' actions thus helped improve the opinion extraction algorithm.
000197180 700__ $$aMusat, Claudiu Cristian
000197180 700__ $$0240959$$aFaltings, Boi$$g105074
000197180 7112_ $$aTwenty-Seventh AAAI Conference on Artificial Intelligence
000197180 8564_ $$s574063$$uhttps://infoscience.epfl.ch/record/197180/files/6710.pdf$$yn/a$$zn/a
000197180 909C0 $$0252184$$pLIA$$xU10406
000197180 909CO $$ooai:infoscience.tind.io:197180$$pconf$$pIC$$qGLOBAL_SET
000197180 917Z8 $$x208605
000197180 937__ $$aEPFL-CONF-197180
000197180 973__ $$aEPFL$$rNON-REVIEWED$$sPUBLISHED
000197180 980__ $$aCONF