I search for applications about recommender systems where there is Similarity techniques in the field of agriculture .
Idea in general it is to use algorithms which gives according to historical data of the classifications of soil. then make a mapping spell between the existing data of soil, weather and crops and an input entered, user to know the type of crop adapted to his soil in addition to that the amount of appropriate fertilizer. my question targets similarity systems and their uses in these applications.
If you have articles or links on this topic it will be very helpful.
Your question is bit unclear , please elaborate further. Our prime objective is to have a minimum variation in fertilizer recomemndation ., regardless of system of recommendation .....
I suggest you some good reading related to your query as Article A scientometric review of emerging trends and new developmen...
https://link.springer.com/chapter/10.1007/978-94-011-5450-5_55
https://www.ijcseonline.org/pub_paper/20-IJCSE-02773.pdf
You might want to check out this paper:
"Sentence similarity based on semantic nets and corpus statistics (PDF)"
they have implemented the algorithm described. their context was very general (effectively any two English sentences) and they found the approach taken was too slow and the results, while promising, not good enough (or likely to be so without considerable, extra, effort).
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