Quickly moving to a new area of research is painful for researchers due to the vast amount of scientific literature in each field of study. One possible way to overcome this problem is to summarize a scientific topic. In this paper, we propose a model of summarizing a single article, which can be further used to summarize an entire topic. Our model is based on analyzing others' viewpoint of the target article's contributions and the study of its citation summary network using a clustering approach.
To summarize a scientific paper, REF presented two sentence selection strategies based on the clusters which were generated by a hierarchical agglomeration algorithm applied in the citation summary network.
Scientific Paper Summarization Using Citation Summary Networks
International Conference On Computational Linguistics
Computer Science