  Future works in scientific articles are valuable for researchers and they can
guide researchers to new research directions or ideas. In this paper, we mine
the future works in scientific articles in order to 1) provide an insight for
future work analysis and 2) facilitate researchers to search and browse future
works in a research area. First, we study the problem of future work extraction
and propose a regular expression based method to address the problem. Second,
we define four different categories for the future works by observing the data
and investigate the multi-class future work classification problem. Third, we
apply the extraction method and the classification model to a paper dataset in
the computer science field and conduct a further analysis of the future works.
Finally, we design a prototype system to search and demonstrate the future
works mined from the scientific papers. Our evaluation results show that our
extraction method can get high precision and recall values and our
classification model can also get good results and it outperforms several
baseline models. Further analysis of the future work sentences also indicates
interesting results.
