Supervised Sequence Segmentation Algorithm: Difference between revisions
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** It can, based on the [[task domain]], be: a [[Supervised Text Segmentation Algorithm]], a [[Supervised DNA Segmentation Algorithm]], .... | ** It can, based on the [[task domain]], be: a [[Supervised Text Segmentation Algorithm]], a [[Supervised DNA Segmentation Algorithm]], .... | ||
* <B>Example(s):</B> | * <B>Example(s):</B> | ||
** a [[Semi-Markov CRFs]] | ** a [[Semi-Markov CRFs]]. | ||
* <B>Counter-Example(s):</B> | * <B>Counter-Example(s):</B> | ||
** a [[Dictionary-based Sequence Segmentation Algorithm]]. | ** a [[Dictionary-based Sequence Segmentation Algorithm]]. |
Revision as of 18:42, 4 October 2023
A Supervised Sequence Segmentation Algorithm is a sequence segmentation algorithm that is a supervised classification algorithm and that can be implemented into a Supervised Sequence Segmentation System (to solve a Supervised Sequence Segmentation Task).
- Context:
- It can be applied by a Supervised Sequence Segmentation System (that can solve a supervised sequence segmentation task).
- It can, based on the task domain, be: a Supervised Text Segmentation Algorithm, a Supervised DNA Segmentation Algorithm, ....
- Example(s):
- Counter-Example(s):
- See: Supervised Sequence Recognition Task.
References
2006
- (Sarawagi, 2006) ⇒ Sunita Sarawagi. (2006). “Efficient Inference on Sequence Segmentation Models.” In: Proceedings of the 23rd International Conference on Machine Learning (ICML 2006). doi:10.1145/1143844.1143944