@InProceedings{qwaider-freihat-giunchiglia:2017:SemEval,
  author    = {Qwaider, Mohammed R. H.  and  Freihat, Abed Alhakim  and  Giunchiglia, Fausto},
  title     = {TrentoTeam at SemEval-2017 Task 3: An application of Grice Maxims in Ranking Community Question Answers},
  booktitle = {Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)},
  month     = {August},
  year      = {2017},
  address   = {Vancouver, Canada},
  publisher = {Association for Computational Linguistics},
  pages     = {271--274},
  abstract  = {In   this   paper   we                                 present               the     
	        
	Tren-toTeam  system  which
	participated  to  thetask  3  at  SemEval-2017                                (Nakov 
	     
	et 
	al.,2017).We 
	concentrated  our  work  onapplying   Grice   Maxims(used   in                       
	     
	manystate-of-the-art Machine learning applica-tions(Vogel  et  al.,  2013; 
	Kheirabadiand  Aghagolzadeh,  2012;  Dale  and                               
	Re-iter,     
	1995;  Franke, 
	2011))                                to              ranking  an-swers of a question
	by answers
	relevancy.Particularly, 
	we  created  a                                ranker                    systembased on
	relevancy
	scores,
	assigned
	by 3main
	components:  Named entity recogni-tion,  similarity score,  sentiment
	analysis.Our system obtained a comparable resultsto Machine learning systems.},
  url       = {http://www.aclweb.org/anthology/S17-2043}
}