Community-based Cyberreading for Information Understanding
This addresses the challenge for scholars in understanding complex scientific publications, but it appears incremental as it builds on existing collaboration and recommendation techniques.
The paper tackles the problem of scientific information understanding by proposing methods to assist scholars through physical and virtual collaboration, resulting in algorithms for grouping readers and recommending resources to improve comprehension.
Although the content in scientific publications is increasingly challenging, it is necessary to investigate another important problem, that of scientific information understanding. For this proposed problem, we investigate novel methods to assist scholars (readers) to better understand scientific publications by enabling physical and virtual collaboration. For physical collaboration, an algorithm will group readers together based on their profiles and reading behavior, and will enable the cyberreading collaboration within a online reading group. For virtual collaboration, instead of pushing readers to communicate with others, we cluster readers based on their estimated information needs. For each cluster, a learning to rank model will be generated to recommend readers' communitized resources (i.e., videos, slides, and wikis) to help them understand the target publication.