algorithm - Behavioral Analysis : Combining DMOZ categories -


i trying analyse behaviour of user using urls guy has visited , make accurate prediction popular dmoz categories (http://dmoztools.net/).

we have built api maps url dmoz category quite accurately. api looks :

input - url

output - dmoz category in url lies maximum probability , probability value.

after passing urls user has visited api, come dmoz categories , respective probabilities. there may lot of dmoz categories number of input url increases. trying filter out relevant dmoz categories. dmoz category may not returned exactly, instead can limit dmoz hierarchy .

example:

1)

 url1 dmoz -> grocery/vegetable/tomato ,  url2 dmoz -> grocery/vegetable/potato,  url3 dmoz -> grocery/vegetable/onion  expected output : grocery/vegetable (since user interested across vegetables)

2)

url1 dmoz -> grocery/vegetable/tomato ,  url2 dmoz -> grocery/vegetable/tomato,  url3 dmoz -> grocery/vegetable/tomato,  url4 dmoz -> grocery/vegetable/potato  expected output : grocery/vegetable/tomato (since user more biased towards tomato)

as clear above, want filter out dmoz hierarchy has rare significance, giving priority subclasses if significant.is there standard way of merging dmoz categories, make accurate dmoz category predicition user ?


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