Cohesion Grading Decisions in a Summary Evaluation Environment: A Machine Learning Approach
Iraide Zipitria, Basilio Sierra, Ana Arruarte, Jon Ander Elorriaga · eScholarship (California Digital Library) · 2012
The work presented in this paper has been carried out in the context of a summary writing environment provided with au-tomatic grading. Regarding summarisation discourse, some of the most relevant variables identified in previous work are comprehension, adequacy, use of language, coherence, and co-hesion. This work is focused on cohesion. The described ex-ploratory study starts from basic automatic measures of co-hesion to further analyse which of them best reflects human expert overall cohesion grades for learner summaries written in the Basque language. For this purpose, 45 basic cohesion measures are compared to overall human cohesion grades. Ma-chine Learning techniques are used to select the best combina-tion for cohesion grading.