Semantic Clustering
First Claim
1. A method implemented by one or more modules at least partially by hardware, the method comprising:
- producing a plurality of semantic graphs based on linguistic analysis of a corpus; and
clustering the plurality of semantic graphs into a plurality of semantic clusters through use of one or more proximity metrics.
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Accused Products
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.
431 Citations
32 Claims
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1. A method implemented by one or more modules at least partially by hardware, the method comprising:
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producing a plurality of semantic graphs based on linguistic analysis of a corpus; and clustering the plurality of semantic graphs into a plurality of semantic clusters through use of one or more proximity metrics. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21)
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22. A method implemented by one or more modules at least partially by hardware, the method comprising:
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forming a plurality of semantic clusters from a corpus that includes a plurality of user utterances, the semantic clusters identifying the user utterances that correspond to like topics based on a linguistic analysis of the corpus; and representing one or more of the plurality of semantic clusters in a graphical user interface as providing a quantitative indication of prevalence of the topics in the corpus. - View Dependent Claims (23, 24, 25, 26, 27, 28, 29, 30)
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31. One or more computer-readable media comprising instructions stored thereon that, responsive to execution by a computing device, causes the computing device to perform operations comprising:
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clustering a plurality of semantic graphs formed from utterances in a corpus using one or more linguistic techniques to form semantic clusters, each said semantic cluster corresponding to a topic; and outputting in a graphical user interface a representation of a ratio of the utterances that were clustered versus the utterances from the corpus that were not clustered. - View Dependent Claims (32)
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Specification