Argumentative Classiication of Extracted Sentences as a Rst Step towards Exible Abstracting

Argumentative Classification of Extracted Sentences as a First Step towards Flexible Abstracting

Sentence Extraction and Rhetorical Classiication for Exible Abstracts

Knowledge about the discourse-level structure of a sci-entiic article is useful for exible and sub-domain independent automatic abstraction. We are interested in the automatic identiication of content units (\argu-mentative entities") in the source text, such as Goal or Problem Statement, Conclusions and Results. In this paper, we present an extension of Ku-piec et al.'s methodology for trainab...

An annotation scheme for discourse-level argumentation in research articles

In order to build robust automatic abstracting systems, there is a need for better training resources than are currently available. In this paper, we introduce an annotation scheme for scientific articles which can be used to build such a resource in a consistent way. The seven categories of the scheme are based on rhetorical moves of argumentation. Our experimental results show that the scheme...

Content-Based Classi cation and Retrieval of Audio

An online audio classiication and segmentation system is presented in this research, where audio recordings are classiied and segmented into speech, music, several types of environmental sounds and silence based on audio content analysis. This is the rst step of our continuing work towards a general content-based audio classiication and retrieval system. The extracted audio features include tem...

Context-aware Argumentative Relation Mining

Context is crucial for identifying argumentative relations in text, but many argument mining methods make little use of contextual features. This paper presents contextaware argumentative relation mining that uses features extracted from writing topics as well as from windows of context sentences. Experiments on student essays demonstrate that the proposed features improve predictive performanc...