I am looking for a formula/algorithm that encompasses the items below and delivers a match score based on the quality of items that match the criterion:
1. The number of variables (let’s call them criterion) can change. There can be as little as 3 criterion and as many as 100 criterion.
2. The weight applied to each criteria can range from 0-100% and each criteria is independent of the other criterion. (eg. multiple criterion can have the same weight- let's say the weight for 4 matching criteria is 60%, weight for 10 matching criteria is set to 75%, 1 is set to 90%, and 2 are set to 10%. Note this is only an example and the weight and number of matching criteria can changed/set by each user).
I am looking for an algorithm that allows for any number of match criteria to be applied by the weight assigned to each criteria for one dataset to unstructured data. The algorithm must be flexible allowing for any number of criteria to be added.
The algorithm will be applied to large sets of unstructured data and ideally can be updated based on match search results that are selected as good matches by the user. Think of Pandora where based on the "like/dislike" feature, Pandora finds other songs that fit your 'like' category. Similarly if a user likes the match results they can select 'like' which then should update the algorithm (match criteria is updated based on the criteria and match for the favorable result).
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I am a Mechatronics engineering student with considerably expertise knowledge in the job you posted. I have good programming skills in java,c#,python,Eclipse,C++ and [url removed, login to view] meeting is also assured as I can promise Daha fazlası
This can be done. I have 6 years of experience including 4 years of programming experience in c++. Do let me know in case of further interest.