| 发明名称 |
SYSTEMS AND METHODS FOR LEARNING SEMANTIC PATTERNS FROM TEXTUAL DATA |
| 摘要 |
In some embodiments, a system is provided comprising at least one processor programmed to process an input text to identify a plurality of semantic patterns that match the input text, wherein, for at least one semantic pattern of the plurality of semantic patterns: the at least one semantic pattern comprises a plurality of semantic entities identified from the at least one input text, and the plurality of semantic entities occur in a common context within the at least one input text. The at least one processor may be further programmed to use statistical information derived from training data to associate a respective weight with each semantic pattern of the plurality of semantic patterns. |
| 申请公布号 |
US2016364476(A1) |
申请公布日期 |
2016.12.15 |
| 申请号 |
US201514737379 |
申请日期 |
2015.06.11 |
| 申请人 |
Nuance Communications, Inc. |
发明人 |
Curin Jan |
| 分类号 |
G06F17/30;G06N99/00 |
主分类号 |
G06F17/30 |
| 代理机构 |
|
代理人 |
|
| 主权项 |
1. A system comprising at least one processor programmed to:
process an input text to identify a plurality of semantic patterns that match the input text, wherein, for at least one semantic pattern of the plurality of semantic patterns:
the at least one semantic pattern comprises a plurality of semantic entities identified from the at least one input text, andthe plurality of semantic entities occur in a common context within the at least one input text; and use statistical information derived from training data to associate a respective weight with each semantic pattern of the plurality of semantic patterns. |
| 地址 |
Burlington MA US |
