Data Science Asked on January 11, 2021
I am a computer science student working on a small information retrieval project. I have a dictionary with a domain as a key and it’s ranking as value.
Based on that ranking, I need to score every domains. I was thinking to do 1/ranking but the disparity is too high. For example the first domain will have a score of 1 (1/1) and the domain ranked 10th will have a score of 0.1 which does not make sense for this.
I have 1000 domains in total and the last one should be close to 0.10 and the first one close to 1
You are essentially asking how Google calculates the score of the domains. The correspondence of the score with ranking is different for every search. Sometimes it is closer to x(i) = alpha*x(i-1)
(exponential weights). Sometimes it could be linear x(i) = (n-i)*2/((n+1)*n)
. I've seen some papers that just use the number of the ranking for regression (linear), but this was not about internet domains, but some other topic.
I will try to answer the question about your weights and you weighting system:
You are using 1/1, 1/2, 1/3 ... 1/100 ... 1/1000
Instead you could use 1/1, 1/1.01, 1/1.02, 1/1.03 ... 1/2 ... 1/10
So your weights are $$weights = frac{1}{1+ranking*0.01*frac{9}{9.99}}$$ where ranking starts with 0 and ends with 999
Answered by keiv.fly on January 11, 2021
Get help from others!
Recent Answers
Recent Questions
© 2024 TransWikia.com. All rights reserved. Sites we Love: PCI Database, UKBizDB, Menu Kuliner, Sharing RPP