Comments (4)
@usptact Yeah, in my case for each item there is a set of features which contains possible tag set.
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Perhaps I don't understand your problem but to me CRF is about what tags are possible for each item given some training set. In other words, your model learns what are the most likely tags at each item in the sequence. Finally, a priori one does not generally know at which element are the likely tags.
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@usptact the reason to restrict a number of tags is efficiency: you may have 1000 tags in your tag set, but only 5 possible tags for an item according to a dictionary. Time complexity is O(N^2) regarding to a number of tags, so the effect can be pretty large.
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@kmike Thanks for the clarification! I see the point now. For this to work, if I understand correctly, one must know at which items to restrict the possible tag set.
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