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Determining one or more topics of a conversation using a domain specific model

  • US 8,626,509 B2
  • Filed: 03/26/2008
  • Issued: 01/07/2014
  • Est. Priority Date: 10/13/2006
  • Status: Active Grant
First Claim
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1. A method comprising:

  • receiving a first set of one or more features of at least a first part of a conversation between at least a first speaker and a second speaker;

    comparing, using at least one processor, the first set of one or more features of the at least the first part of the conversation to information regarding a node of a taxonomy of a domain specific model to determine whether the at least the first part of the conversation relates to a topic to which the node of the taxonomy corresponds, wherein the taxonomy of the domain specific model is hierarchical and comprises a plurality of nodes arranged in different levels of a hierarchy, wherein a higher-level node of the taxonomy corresponds to a broad topic and a lower-level node below the higher-level node in the taxonomy corresponds to a specific topic that relates to the broad topic and is more specific than the broad topic, and wherein comparing the first set of one or more features of the at least the first part of the conversation to the information regarding the node comprises comparing the first set of one or more features to information regarding the higher-level node of the taxonomy to determine whether the at least the first part of the conversation relates to the broad topic, wherein the comparing of the first set of one or more features to the information regarding the higher-level node has a first probability of providing a first prediction accuracy in identifying whether the at least the first part of the conversation relates to the broad topic;

    in response to determining that a result of the comparing indicates that the at least the first part of the conversation relates to the broad topic, presenting, to a user interface of a device operated by the first speaker, topic-specific information related to the broad topic;

    receiving a second set of one or more features of at least a second part of the conversation, the second part of the conversation including both the first part of the conversation and a subsequent part occurring in the conversation following the first part;

    in response to determining that the result of the comparing of the first set of the one or more features to the information regarding the higher-level node indicates that the at least the first part of the conversation relates to the broad topic, comparing the second set of one or more features of the first part and the subsequent part to information regarding the lower-level node to determine whether the at least the second part of the conversation relate to the specific topic related to the broad topic, wherein the comparing of the second set of one or more features to the information regarding the lower-level node has a second probability of providing a second prediction accuracy in identifying whether the at least the second part of the conversation relates to the specific topic, the second prediction accuracy being higher than the first prediction accuracy; and

    in response to determining that a result of the comparing of the second set of one or more features to the information regarding the lower-level node indicates that the at least the second part of the conversation relates to the specific topic, presenting to the first speaker topic-specific information related to the specific topic.

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