TY - GEN
T1 - Bootstrap voting experts
AU - Hewlett, Daniel
AU - Cohen, Paul
PY - 2009
Y1 - 2009
N2 - BOOTSTRAP VOTING EXPERTS (BVE) is an extension to the VOTING EXPERTS algorithm for unsupervised chunking of sequences. BVE generates a series of segmentations, each of which incorporates knowledge gained from the previous segmentation. We show that this method of bootstrapping improves the performance of VOTING EXPERTS in a variety of unsupervised word segmentation scenarios, and generally improves both precision and recall of the algorithm. We also show that Minimum Description Length (MDL) can be used to choose nearly optimal parameters for VOTING EXPERTS in an unsupervised manner.
AB - BOOTSTRAP VOTING EXPERTS (BVE) is an extension to the VOTING EXPERTS algorithm for unsupervised chunking of sequences. BVE generates a series of segmentations, each of which incorporates knowledge gained from the previous segmentation. We show that this method of bootstrapping improves the performance of VOTING EXPERTS in a variety of unsupervised word segmentation scenarios, and generally improves both precision and recall of the algorithm. We also show that Minimum Description Length (MDL) can be used to choose nearly optimal parameters for VOTING EXPERTS in an unsupervised manner.
UR - http://www.scopus.com/inward/record.url?scp=78751681397&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=78751681397&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:78751681397
SN - 9781577354260
T3 - IJCAI International Joint Conference on Artificial Intelligence
SP - 1071
EP - 1076
BT - IJCAI-09 - Proceedings of the 21st International Joint Conference on Artificial Intelligence
PB - International Joint Conferences on Artificial Intelligence
T2 - 21st International Joint Conference on Artificial Intelligence, IJCAI 2009
Y2 - 11 July 2009 through 16 July 2009
ER -