Difference between revisions of "Hall emnlp2008"
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== Model == | == Model == | ||
| − | LDA with post hoc analysis to calculate observed probability of topics in the current year | + | LDA with post hoc analysis to calculate observed probability of topics in the current year <br> |
<math> | <math> | ||
\hat{p}(z|y) = \sum_{d:t_d=y} \hat{p}(z|d) \hat{p}(d|y) | \hat{p}(z|y) = \sum_{d:t_d=y} \hat{p}(z|d) \hat{p}(d|y) | ||
Revision as of 15:54, 1 April 2011
Paper
- Title : Studying the History of Ideas Using Topic Models
- Authors : D. Hall, D. Jurafsky, and C. D. Manning
- Venue : EMNLP 2008
Summary
This paper uses topic models to study the development of ideas over time for papers in computational linguistics conferences (ACL, COOLING, EMNLP, etc.)
Dataset
ACL Anthology (~12,500 papers)
Model
LDA with post hoc analysis to calculate observed probability of topics in the current year
I is the indication function, t_d is the date document d was published, p(d|y) is a constant 1/C
Experiments
- Ran 100 topics LDA, took relevant 36 topics.
- Seeded words for 10 more topics to improve coverage.
- Used these 36+10 topics as priors for new 100-topics run.
- Picked 43 topics and manually labeled them.
Results
- Trending topics in the CL community
- Declining topics in the CL community
- NLP applications
They investigated whether CL is becoming more applied over time.
They explored six applicatons : Machine Translation, Spelling Correction, Dialogue Systems, Call Routing, Speech Recognition, and Biomedical
- ACL vs COLING vs EMNLP
