Semi-Markov Conditional Random Field

References

(Wikipedia, 2015) ⇒ http://en.wikipedia.org/wiki/Markov_renewal_process Retrieved:2015-6-17.
- In probability and statistics a Markov renewal process is a random process that generalizes the notion of Markov jump processes. Other random processes like Markov chain, Poisson process, and renewal process can be derived as a special case of an MRP (Markov renewal process).

(Sarawagi & Cohen, 2004) ⇒ Sunita Sarawagi, and William W. Cohen. (2004). “Semi-Markov Conditional Random Fields for Information Extraction.” In: Proceedings of Advances in Neural Information Processing Systems, 17 NIPS 2004.
- QUOTE: We describe semi-Markov conditional random-fields (semi-CRFs), a conditionally trained version of semi-Markov chains. Intuitively, a semi-CRF on an Input sequence [math]\displaystyle{ \bf{x} }[/math] outputs a “segmentation” of [math]\displaystyle{ \bf{x} }[/math], in which labels are assigned to segments (i.e., subsequences) of [math]\displaystyle{ \bf{x} }[/math] rather than to individual elements [math]\displaystyle{ x_i }[/math] of [math]\displaystyle{ \bf{x} }[/math]. Importantly, features for semi-CRFs can measure properties of segments, and transitions within a segment can be non-Markovian. ...