{"title":"Well, to Be Honest, I Wouldnt Start from Here at All","authors":"P. Dunne","doi":"10.3233/FAIA220134","DOIUrl":"https://doi.org/10.3233/FAIA220134","url":null,"abstract":"","PeriodicalId":36616,"journal":{"name":"Comma","volume":"1 1","pages":"3-14"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84112771","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Stefan Ellmauthaler, S. A. Gaggl, Dominik Rusovac, J. Wallner
{"title":"ADF-BDD: An ADF Solver Based on Binary Decision Diagrams","authors":"Stefan Ellmauthaler, S. A. Gaggl, Dominik Rusovac, J. Wallner","doi":"10.3233/FAIA220170","DOIUrl":"https://doi.org/10.3233/FAIA220170","url":null,"abstract":"","PeriodicalId":36616,"journal":{"name":"Comma","volume":"13 1","pages":"355-356"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82029626","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Argumentation: From Theory to Practice & Back","authors":"A. Kakas","doi":"10.3233/FAIA220136","DOIUrl":"https://doi.org/10.3233/FAIA220136","url":null,"abstract":"","PeriodicalId":36616,"journal":{"name":"Comma","volume":"1 1","pages":"16-17"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88131184","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"On the Impact of Data Selection when Applying Machine Learning in Abstract Argumentation","authors":"Isabelle Kuhlmann, Thorsten Wujek, Matthias Thimm","doi":"10.3233/FAIA220155","DOIUrl":"https://doi.org/10.3233/FAIA220155","url":null,"abstract":". We examine the impact of both training and test data selection in ma- chine learning applications for abstract argumentation, in terms of prediction accuracy and generalizability. For that, we first review previous studies from a data- centric perspective and conduct some experiments to back up our analysis. We further present a novel algorithm to generate particularly challenging argumentation frameworks wrt. the task of deciding skeptical acceptability under preferred semantics. Moreover, we investigate graph-theoretical aspects of the existing datasets and perform some experiments which show that some simple properties (such as in-degree and out-degree of an argument) are already quite strong indicators of whether or not an argument is skeptically accepted under preferred semantics.","PeriodicalId":36616,"journal":{"name":"Comma","volume":"38 1","pages":"224-235"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72673281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"PyArg for Solving and Explaining Argumentation in Python: Demonstration","authors":"A. Borg, D. Odekerken","doi":"10.3233/FAIA220167","DOIUrl":"https://doi.org/10.3233/FAIA220167","url":null,"abstract":". We introduce PyArg , a Python-based solver and explainer for both abstract argumentation and ASPIC + . A large variety of extension-based semantics allows for flexible evaluation and several explanation functions are available.","PeriodicalId":36616,"journal":{"name":"Comma","volume":"945 1","pages":"349-350"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77570051","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Treewidth for Argumentation Frameworks with Collective Attacks","authors":"W. Dvořák, Matthias König, S. Woltran","doi":"10.3233/FAIA220148","DOIUrl":"https://doi.org/10.3233/FAIA220148","url":null,"abstract":"","PeriodicalId":36616,"journal":{"name":"Comma","volume":"21 1","pages":"140-151"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86090829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"User-Centric Argument Mining with ArgueMapper and Arguebuf","authors":"Mirko Lenz, R. Bergmann","doi":"10.3233/FAIA220176","DOIUrl":"https://doi.org/10.3233/FAIA220176","url":null,"abstract":"","PeriodicalId":36616,"journal":{"name":"Comma","volume":"57 1","pages":"367-368"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84000236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Milad Alshomary, Jonas Rieskamp, Henning Wachsmuth
{"title":"Generating Contrastive Snippets for Argument Search","authors":"Milad Alshomary, Jonas Rieskamp, Henning Wachsmuth","doi":"10.3233/FAIA220138","DOIUrl":"https://doi.org/10.3233/FAIA220138","url":null,"abstract":". In argument search, snippets provide an overview of the aspects discussed by the arguments retrieved for a queried controversial topic. Existing work has focused on generating snippets that are representative of an argument’s content while remaining argumentative. In this work, we argue that the snippets should also be contrastive , that is, they should highlight the aspects that make an argument unique in the context of others. Thereby, aspect diversity is increased and redundancy is reduced. We present and compare two snippet generation approaches that jointly optimize representativeness and contrastiveness. According to our experiments, both approaches have advantages, and one is able to generate representative yet sufficiently contrastive snippets.","PeriodicalId":36616,"journal":{"name":"Comma","volume":"62 1","pages":"21-31"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80488316","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}