Systems and methods for learning semantic patterns from textual data
AssigneeNuance Communications, Inc.
InventorJan Curin
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Abstract
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.
Claims20
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 valency frame having a plurality of valency frame components;
- the plurality of valency frame components correspond, respectively, to 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;
- and
- use statistical information derived from training data to associate a respective weight with each semantic pattern of the plurality of semantic patterns, wherein, for the at least one semantic pattern, the statistical information comprises at least one measure of mutual information derived from the training data.
A method comprising acts of:
- processing 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 valency frame having a plurality of valency frame components;
- the plurality of valency frame components correspond, respectively, to 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;
- and
- using statistical information derived from training data to associate a respective weight with each semantic pattern of the plurality of semantic patterns, wherein, for the at least one semantic pattern, the statistical information comprises at least one measure of mutual information derived from the training data.
At least one computer-readable medium having encoded thereon instructions which, when executed by at least one processor, cause the at least one processor to perform a method comprising acts of:
- processing 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 valency frame having a plurality of valency frame components;
- the plurality of valency frame components correspond, respectively, to 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;
- and
- using statistical information derived from training data to associate a respective weight with each semantic pattern of the plurality of semantic patterns, wherein, for the at least one semantic pattern, the statistical information comprises at least one measure of mutual information derived from the training data.
Dependencies are inferred from the claim text.