Supporting the generation of argument structure within video sequences

Browsing is a useful way of exploring annotated media repositories. Sets of links can be automatically created from the annotations associated with the media items in the repository. When there are also relationships among the annotations themselves, such as when the annotation terms are part of a thesaurus, these relations can also be used in the link generation process. Using structured annotations and a thesaurus for generating link sets has two advantages. The first is to evaluate the effectiveness of the terms in the thesaurus for classifying the media items in the repository. The second is to be able to control the links being generated by changing relationships within the thesaurus. The work is illustrated using video segments annotated with argument structures, but we show that the method used is independent of the media types and applicable to systems that use similar annotation structures and typed relations among the

Supporting the generation of argument structure within video sequences

Browsing is a useful way of exploring annotated media repositories. Sets of links can be automatically created from the annotations associated with the media items in the repository. When there are also relationships among the annotations themselves, such as when the annotation terms are part of a thesaurus, these relations can also be used in the link generation process. Using structured annotations and a thesaurus for generating link sets has two advantages. The first is to evaluate the effectiveness of the terms in the thesaurus for classifying the media items in the repository. The second is to be able to control the links being generated by changing relationships within the thesaurus. The work is illustrated using video segments annotated with argument structures, but we show that the method used is independent of the media types and applicable to systems that use similar annotation structures and typed relations among the

A rubric based approach towards Automated Essay Grading : focusing on high level content issues and ideas

Assessment of a student’s work is by no means an easy task. Even if the student response is in the form of multiple choice answers, manually marking those answer sheets is a task that most teachers regard as rather tedious. The development of an automated method to grade these essays was thus an inevitable step.This thesis proposes a novel approach towards Automated Essay Grading through the use of various concepts found within the field of Narratology. Through a review of the literature, several methods in which essays are graded were identified together with some of the problems. Mainly, the issues and challenges that plague AEG systems were that those following the statistical approach needed a way to deal with more implicit features of free text, while other systems which did manage that were highly dependent on the type of student response, the systems having pre-knowledge pertaining to the subject domain in addition to requiring more computational power. It was also found that while narrative essays are one of the main methods in which a student might be able to showcase his/her mastery over the English language, no system thus far has attempted to incorporate narrative concepts into analysing these type of free text responses.It was decided that the proposed solution would be centred on the detection of Events, which was in turn used to determine the score an essay receives under the criteria of Audience, Ideas, Character and Setting and Cohesion, as defined by the NAPLAN rubric. From the results gathered from experiments conducted on the four criteria mentioned above, it was concluded that the concept of detecting Events as they were within a narrative type story when applied to essay grading, does have a relation towards the score the essay receives. All experiments achieved an average F-measure score of 0.65 and above while exact agreement rates were no lower than 70%. Chi-squared and paired T-test values all indicated that there was insufficient evidence to show that there was any significant difference between the scores generated by the computer and those of the human markers

ABSTRACT Supporting the Generation of Argument Structure within Video Sequences

We describe our approach to the automatic generation of argument structures in the domain of video documentaries. Our approach releases control of the final video sequencing from the film maker/annotator to the system and thus allows users to select their own documentaries for viewing. Each video segment is annotated using a formal structure filled in with terms from a thesaurus. The annotations are used for finding and combining video segments into a final presentation. In order to influence the documentaries that can be generated, we introduce three methods for the annotator to evaluate the effectiveness of the annotations and to influence the process of automatic link generation