Performing linguistic analysis by scoring syntactic graphs
First Claim
1. A computer-implemented method of improving performance of linguistic processing by an automated conversational agent, the method comprising:
- mapping sequences of one or more user utterances to lemmata, the one or more user utterances containing variations in lexical form, thereby yielding mapped lemmata;
unifying constructions of the mapped lemmata to generate one or more syntactic graphs;
scoring each of the one or more syntactic graphs based on confidence in the syntactic graph'"'"'s recognition of particular constructions of the lemmata, the particular constructions including syntactic patterns linking a given lemma to one or more other lexical items;
using a given syntactic graph with a highest determined score in an abstracted semantic graph of the one or more user utterances;
providing the abstracted semantic graph to the automated conversational agent in a format that enables the automated conversational agent to employ the abstracted semantic graph; and
participating, by the automated conversational agent, in an interactive natural language dialog with a user by the employed abstracted semantic graph recognizing and processing user utterances having variations in lexical form.
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Abstract
Semantic clustering techniques are described. In various implementations, a conversational agent is configured to perform semantic clustering of a corpus of user utterances. Semantic clustering may be used to provide a variety of functionality, such as to group a corpus of utterances into semantic clusters in which each cluster pertains to a similar topic. These clusters may then be leveraged to identify topics and assess their relative importance, as for example to prioritize topics whose handling by the conversation agent should be improved. A variety of utterances may be processed using these techniques, such as spoken words, textual descriptions entered via live chat, instant messaging, a website interface, email, SMS, a social network, a blogging or micro-blogging interface, and so on.
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Citations
19 Claims
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1. A computer-implemented method of improving performance of linguistic processing by an automated conversational agent, the method comprising:
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mapping sequences of one or more user utterances to lemmata, the one or more user utterances containing variations in lexical form, thereby yielding mapped lemmata; unifying constructions of the mapped lemmata to generate one or more syntactic graphs; scoring each of the one or more syntactic graphs based on confidence in the syntactic graph'"'"'s recognition of particular constructions of the lemmata, the particular constructions including syntactic patterns linking a given lemma to one or more other lexical items; using a given syntactic graph with a highest determined score in an abstracted semantic graph of the one or more user utterances; providing the abstracted semantic graph to the automated conversational agent in a format that enables the automated conversational agent to employ the abstracted semantic graph; and participating, by the automated conversational agent, in an interactive natural language dialog with a user by the employed abstracted semantic graph recognizing and processing user utterances having variations in lexical form. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A computer system for improving performance of linguistic processing by an automated conversational agent, the system comprising:
one or more computer processors operatively coupled to computer memory, the one or more processors configured to; map sequences of one or more user utterances to lemmata, the one or more user utterances containing variations in lexical form, thereby yielding mapped lemmata; unify constructions of the mapped lemmata to generate one or more syntactic graphs; score each of the one or more syntactic graphs based on confidence in the syntactic graph'"'"'s recognition of particular constructions of the lemmata, the particular constructions including syntactic patterns linking a given lemma to one or more other lexical items; use a given syntactic graph with a highest determined score in an abstracted semantic graph of the one or more user utterances; and provide the abstracted semantic graph to the automated conversational agent in a format that enables the automated conversational agent to employ the abstracted semantic graph; and participate, by the automated conversational agent, in an interactive natural language dialog with a user by the employed abstracted semantic graph recognizing and processing user utterances having variations in lexical form. - View Dependent Claims (11, 12, 13, 14, 15, 16, 17, 18)
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19. One or more non-transitory computer-readable media comprising instructions stored thereon that, responsive to execution by a computing device, causes the computing device to improve performance of linguistic processing by an automated conversational agent by:
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mapping sequences of one or more user utterances to lemmata, the one or more user utterances containing variations in lexical form, thereby yielding mapped lemmata; unifying constructions of the mapped lemmata to generate one or more syntactic graphs; scoring each of the one or more syntactic graphs based on confidence in the syntactic graph'"'"'s recognition of particular constructions of the lemmata, the particular constructions including syntactic patterns linking a given lemma to one or more other lexical items; using a given syntactic graph with a highest determined score in an abstracted semantic graph of the one or more user utterances; providing the abstracted semantic graph to the automated conversational agent in a format that enables the automated conversational agent to employ the abstracted semantic graph; and participating, by the automated conversational agent, in an interactive natural language dialog with a user by the employed abstracted semantic graph recognizing and processing user utterances having variations in lexical form.
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Specification