%0 Generic %1 levycontext %A Levy, Ran %A Bilu, Yonatan %A Hershcovich, Daniel %A Aharoni, Ehud %A Slonim, Noam %D 2014 %K ml %T Context Dependent Claim Detection %U http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.662.8173 %X While discussing a concrete controversial topic, most humans will find it challenging to swiftly raise a diverse set of convincing and relevant claims that should set the basis of their arguments. Here, we formally define the challenging task of automatic claim detection in a given context and discuss its associated unique difficulties. Further, we outline a preliminary solution to this task, and assess its performance over annotated real world data, collected specifically for that purpose over hundreds of Wikipedia articles. We report promising results of a supervised learning approach, which is based on a cascade of classifiers designed to properly handle the skewed data which is inherent to the defined task. These results demonstrate the viability of the introduced task. 1

@misc{levycontext, abstract = {While discussing a concrete controversial topic, most humans will find it challenging to swiftly raise a diverse set of convincing and relevant claims that should set the basis of their arguments. Here, we formally define the challenging task of automatic claim detection in a given context and discuss its associated unique difficulties. Further, we outline a preliminary solution to this task, and assess its performance over annotated real world data, collected specifically for that purpose over hundreds of Wikipedia articles. We report promising results of a supervised learning approach, which is based on a cascade of classifiers designed to properly handle the skewed data which is inherent to the defined task. These results demonstrate the viability of the introduced task. 1}, added-at = {2016-11-28T13:51:04.000+0100}, author = {Levy, Ran and Bilu, Yonatan and Hershcovich, Daniel and Aharoni, Ehud and Slonim, Noam}, biburl = {https://www.bibsonomy.org/bibtex/2730ba48b81c64cb65d5f5d54140ccc6b/machinelearning}, description = {CiteSeerX — Context Dependent Claim Detection}, interhash = {2234bf322fd96eb3c1c22d5de051dfc1}, intrahash = {730ba48b81c64cb65d5f5d54140ccc6b}, keywords = {ml}, timestamp = {2016-11-28T14:43:56.000+0100}, title = {Context Dependent Claim Detection}, url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.662.8173}, year = 2014 }