Recommendation system
78 USD Constant parameters:
- location (latitude, longitude)
- Services provided (massive)
- Price of a specific service
- estimated time of service delivery
Dynamic parameters:
- Free slots
We have a client list that has
Dynamic parameters:
- location (latitude, longitude)
- desired service
- maximum price of this service
- estimated time of service delivery
You need to generate the master's best recommendation based on input information from the client.
Incoming information from client:
- location (latitude, longitude)
- desired service
- maximum price of this service
- estimated time of service delivery
Priority (minimum procedure time, minimum price, minimum distance)
In a situation where the sample does not contain a master who provides the service selected by the user, recommend a master who provides the most similar service as originally required.
The architecture proposal (it does not necessarily have to be this):
- make a classification that will define the user class on the input information basis (region X1_econom, area X1_standard, area X1_econom_rapid, area X2_standard, etc.)
- the masters must be marked with these marks in the first place.
- make a recommendation based on the average user ' s user ' s user ' s user ' s user ' s user ' s user ' s name (may be via the kosaye base of similerity )
- Priority may be taken into account in the filter
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Odessa