发明名称 |
TRAINING SYSTEMS AND METHODS FOR SEQUENCE TAGGERS |
摘要 |
Systems and methods for or training a sequence tagger, such as conditional random field model. More specifically, the systems and methods train a sequence tagger utilizing partially labeled data from crowd-sourced data for a specific application and partially labeled data from search logs. Further, the systems and methods disclosed herein train a sequence tagger utilizing only partially labeled by utilizing a constrained lattice where each input value within the constrained lattice can have multiple candidate tags with confidence scores. Accordingly, the systems and methods provide for a more accurate sequence tagging system, a more reliable sequence tagging system, and a more efficient sequence tagging system in comparison to sequence taggers trained utilizing at least some fully-labeled training data. |
申请公布号 |
WO2016133696(A1) |
申请公布日期 |
2016.08.25 |
申请号 |
WO2016US16245 |
申请日期 |
2016.02.03 |
申请人 |
MICROSOFT TECHNOLOGY LICENSING, LLC |
发明人 |
JEONG, Minwoo;KIM, Young-Bum;SARIKAYA, Ruhi |
分类号 |
G06N7/00;G06F17/27 |
主分类号 |
G06N7/00 |
代理机构 |
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代理人 |
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主权项 |
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地址 |
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