OpeNTF / README.md
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---
language:
- en
tags:
- machine-learning
- neural-team-formation
pretty_name: 'OpeNTF: An Open-Source Neural Team Formation Benchmark Library'
---
# File Structure
- each training set will have it's own `teamsvecs.pkl` file that can be accessed through the following file path:
- the file structure is identical to that in the OpeNTF github repository
```
\---output
| \---{domain} # e.g. dblp
| \---{training dataset} # e.g. toy.dblp.v12.json
| teamsvecs.pkl
```
# Teamsvecs Structure
## Teamsvecs.pkl
```
{
'skill': {spare matrix of n_teams x n_skills},
'member': {sparse matrix of n_teams x n_members},
'loc': {sparse matrix of n_teams x n_locs} // optional
}
```
### skill
- every team in the entire dataset is represented as a row
- every skill in the entire dataset is represented as a column
- **each row represents the skills that everyone on the team possesses**
### member
- every team in the entire dataset is represented as a row
- every member in the entire dataset is represented as a column
- **each row represents all the members for a the given team**
### loc
- every geolocation in the entire dataset is represented as a row
- every skill in the entire dataset is represented as a column
- **each row represents all the geolocations for a given team**
- NOTE: will be set to `None` if the dataset does not include geolocation
## Full Sparse Matrix
- the three sparse matrices from above can be aligned side by side to form a sparse matrix of `n_teams x (n_skills + n_members + n_locs)`
### Example
- team 1 includes members m1 and m2, skills of s2 and s4, and has the geolocation of l2.
- team 2 includes members m2 and m3, skills of s1 and s2, and has the geolocation of l1.
| s1 | s2 | s3 | s4 | m1 | m2 | m3 | l1 | l2 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 0 | 1 | 0 | 1 | 1 | 1 | 0 | 0 | 1 |
| 1 | 1 | 0 | 0 | 0 | 1 | 1 | 1 | 0 |
# Links
- [OpeNTF GitHub Repository](https://github.com/fani-lab/OpeNTF)