Project Proposal
1-2 pages (single space, 1 inch margins):
- Title (try to be as catch as possible).
- List of team members.
- Abstract.
- Intellectual merit (novelties, challenges, observations).
- Broader impact (who will benefit from this research).
10-15 pages (single space, 1 inch margins, w/o references):
- Research goals:
- What you want to and can accomplish during this semester.
- Be as specific as possible. For instance, "improving dependency parsing" is too ambiguous to be a research goal. Instead, you want to write something like, "improving the accuracy of transition-based dependency parsing with selectional branching and dataset aggregation".
- Your research goals must include some kind of novelty. The above example (selectional branching + dataset aggregation) is not a good research goal because it has been already done.
- Background:
- Motivation of this research (why you want to do this research).
- Previous work relevant to this research. For each work, include a brief description about the work, and how your work is distinguished from the previous work.
- If this is a preliminary research to another research, describe how it is related to the other research (e.g., this is a step-work to the CoNLL shared task).
- Proposed work:
- Be specific about your methodology; it must be feasible within this semester. If you are planning to work more after this semester (e.g., Dec. 2015, Jan. 2016), specify the timeline in the following section.
- Specify the dataset and evaluation methods for experiments. The proposal will be considered infeasible unless this part is clear.
- Timeline
- Bi-weekly plans of your research.
- Specify who will do what in each timeline.
- Do not forget to include times for writing the research paper and preparing for the final presentation.
15 minutes presentation followed by 5 minutes discussion.
- Semi-supervised entity extraction - Henry Chen, Johnny Tan.
- Structure-based verb embeddings - Meera Hahn, Reid Kilgore.
- Topic detection in social media - Peng Ji, Robert Meng.
- Active learning in clouds - Rui Jiang.
- Structured learning for AMR parsing - Alex Lutz, Michael Zhai.
- Deep learning for coreference resolution - Mohsen"Salari Sharif Abad, Bonggun Shin.
- Yelp Dataset Challenge: sentiment analysis - Congzheng Song, Hua Xiao.
- Unsupervised scientific entity extraction - Xiaohong Wang, Jason Yang.
