---
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)