I have implemented an multiple weighted sorting method in a photographer booking project (learning project) for recommendation purpose.
The main idea is to order the photographers from best to worst based on the score from the equation.
Three factors:
- Service's price.
- Distance.
- Rating.
The equation (factors has been normalized and weights are arbitrarily chosen as long as their sum is 1):
score = (f1 * w1) + (f2 * w2) + (f3 * w3)
The aspect I want to explore here is how to modify the method so that newcomers won't have disadvantages. Because when new photographers join in, their rating would be 0.0, so basically they will even lose to those photographer who has very low rating point like 1.0, 2.0.
What I have done so far is to define which photographer is new (based on the joining date and number of bookings they had) and then give them full score for rating. But I feel that isn't really a way to do it and still trying to find a better way.
Thanks for your concern!
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