Engineered an advanced NLP model to classify abstract sentences into their respective roles, such as objectives, methods, and results, facilitating researchers in efficiently skimming through literature and focusing on relevant sections. Experimented with five diverse modeling approaches, including a 1D Convolutional model, a Naive Bayes model with pretrained embeddings, a convolutional model with character embeddings, and a hybrid embedding layer combining pretrained token and character embeddings.
-
Notifications
You must be signed in to change notification settings - Fork 0
sumana-2705/Skimlit-project
Folders and files
| Name | Name | Last commit message | Last commit date | |
|---|---|---|---|---|
Repository files navigation
About
Developing an NLP model to classify abstract sentences into the role they play to enable researchers to skim through the literature and dive deeper when necessary
Resources
Stars
Watchers
Forks
Releases
No releases published
Packages 0
No packages published