Recommendation Engine
Provide automated product or service recommendations based on your customers preferences. Several recommendation algorithms are provided. Experiment with the different algorithms to find which produces the best results with your data. You can find more documentation for these algorithms on our website at: http://catalog.algorithms.io/catalog/index?category=/Recommenders.
1 subscribers
9 endpoints
The in-depth APIMemo review for this API hasn't been published yet —
the data below comes straight from the public marketplace listing.
Recommendation Engine endpoints
| Method | Endpoint | Description |
|---|---|---|
| Dataset | ||
| DELETE |
Delete /dataset/id/{id} |
Delete a dataset |
| GET |
List All /dataset |
List all of your datasets and their attributes such as the id |
| POST |
Upload /dataset |
Upload a dataset |
| GET |
Get One /dataset/id/{id} |
Get the content of a dataset by an id. |
| Step 1 - Prepare Data File | ||
| POST |
Data File Preparation /jobs/run/29 |
This function formats a data file to be compatible with the recommendation algorithms. Currently you will need to use a cURL command to execute this function as it does not work… |
| Step 2 - Run Recommendation | ||
| POST |
Item Based - Pearson Correlation /jobs/run/19 |
Item based recommenders make recommendations based on similarity of items. If item X is similiar to item Y, and person A likes an item X, then person A may also like item Y. They… |
| POST |
Item Based - Log Likelihood /jobs/run/14 |
Item based recommenders make recommendations based on similarity of items. If item X is similiar to item Y, and person A likes an item X, then person A may also like item Y. They… |
| POST |
User Based - Pearson Correlation /jobs/run/40 |
User based recommenders make recommendations based on similarity of users. If person A is similiar to person B, and person B likes an item X, then person A may also like item X.… |
| POST |
User Based - Log Likelihood /jobs/run/18 |
User based recommenders make recommendations based on similarity of users. If person A is similiar to person B, and person B likes an item X, then person A may also like item X.… |
Recommendation Engine pricing
| Plan | Price | Rate limit | Quotas |
|---|---|---|---|
| BASIC | Free | — |
|
| PRO | $9 / month | — |
|
