Abstract: Applications of a domain specific model are described. A domain specific model may encode information about a domain. Information available in the domain specific model may be used to identify a topic of a conversation, such as a topic of a call to a call center. Callers' complaints can be categorized into coarse as well as fine topic categories by analyzing an initial part of a call and by examining a distribution of topic specific descriptive and discriminative features within the initial portion of the call. Once a call has been identified as belonging to a topic, a call-center agent may be prompted with information about the topic, such as questions and answers and actions related to the topic. Generic to specific information may be provided to the agent as the call progresses.

Abstract: A method of building a domain specific model from transcriptions is disclosed. The method starts by applying text clustering to the transcriptions to form text clusters. The text clustering is applied at a plurality of different granularities, and groups topically similar phrases in the transcriptions. The relationship between text clusters resulting from the text clustering at different granularities is then identified to form a taxonomy. The taxonomy is augmented with topic specific information.

Abstract: A method of building a domain specific model from transcriptions is disclosed. The method starts by applying text clustering to the transcriptions to form text clusters. The text clustering is applied at a plurality of different granularities, and groups topically similar phrases in the transcriptions. The relationship between text clusters resulting from the text clustering at different granularities is then identified to form a taxonomy. The taxonomy is augmented with topic specific information.