TY - JOUR
AU - 
AB - ThispaperdescribestheSemEval2016shared task on Aspect Based Sentiment Analysis (ABSA),acontinuationoftherespectivetasks of 2014 and 2015. In its third year, the task provided 19 training and 20 testing datasets for 8 languages and 7 domains, as well as a common evaluation procedure. From these datasets,25wereforsentence-leveland14for text-levelABSA;thelatterwasintroducedfor thefirsttimeasasubtaskinSemEval. Thetask attracted245submissionsfrom29teams. Figure 1: Table summarizing the average sentiment for each aspectof anentity. 1 Introduction Many consumers use the Web to share their experi- method can analyze large amounts of unstructured ences about products, services or travel destinations texts and extract (coarse- or fine-grained) informa- (Yoo and Gretzel, 2008). Online opinionated texts tionnotincludedintheuserratingsthatareavailable (e.g., reviews, tweets) are important for consumer insomereview sites (e.g., Fig. 1). decisionmaking(ChevalierandMayzlin,2006)and Sentiment Analysis (SA) touches every aspect constitute a source of valuable customer feedback (e.g., entity recognition, coreference resolution, that can help companies to measure satisfaction and negation handling) of Natural Language Processing improve their products or services. In this setting, (Liu,2012)andasCambriaetal.(2013)mention“it Aspect Based Sentiment Analysis (ABSA) - i.e., requiresadeepunderstandingoftheexplicitandim- miningopinionsfromtextaboutspecificentitiesand plicit, regular and irregular, and syntactic and se- their aspects (Liu, 2012) - can provide valuable in- mantic language rules”. Within the last few years sightstobothconsumersandbusinesses. AnABSA severalSA-relatedsharedtaskshavebeenorganized *Correspondingauthor: mpontiki@ilsp.gr. in the context of workshops and conferences focus- Proceedings of 
TI - SemEval-2016 Task 5: Aspect Based Sentiment Analysis
JF - Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016)
DO - 10.18653/v1/s16-1002
DA - 2016-01-01
UR - https://www.deepdyve.com/lp/unpaywall/semeval-2016-task-5-aspect-based-sentiment-analysis-SblkNj0VvA
DP - DeepDyve
ER -