1. A method for forming discrete segment clusters of one or more sequential sentences from a corpus of communication transcripts of transactional communications, each communication transcript including a sequence of sentences spoken between a caller and a responder, the method comprising: dividing the communication transcripts of the corpus into a first set of sentences spoken by the caller and a second set of sentences spoken by the responder; using a processor, generating a set of sentence clusters by grouping the first and second sets of sentences according to a measure of lexical similarity using an unsupervised partitional clustering method; generating a collection of sequences of sentence types by assigning a distinct sentence type to each sentence cluster and representing each sentence of each communication transcript of the corpus with the sentence type assigned to the sentence cluster into which the sentence is grouped; and generating a specified number of discrete segment clusters of one or more sequential sentences by successively merging sentence clusters according to a proximity-based measure between the sentence types assigned to the sentence clusters within sequences of the collection.
1. A method for forming discrete segment clusters of one or more sequential sentences from a corpus of communication transcripts of transactional communications, each communication transcript including a sequence of sentences spoken between a caller and a responder, the method comprising: dividing the communication transcripts of the corpus into a first set of sentences spoken by the caller and a second set of sentences spoken by the responder; using a processor, generating a set of sentence clusters by grouping the first and second sets of sentences according to a measure of lexical similarity using an unsupervised partitional clustering method; generating a collection of sequences of sentence types by assigning a distinct sentence type to each sentence cluster and representing each sentence of each communication transcript of the corpus with the sentence type assigned to the sentence cluster into which the sentence is grouped; and generating a specified number of discrete segment clusters of one or more sequential sentences by successively merging sentence clusters according to a proximity-based measure between the sentence types assigned to the sentence clusters within sequences of the collection. 2. The method of claim 1 , wherein the unsupervised partitional clustering method is a K-means algorithm that is performed adaptively by increasing the specified number of sentence clusters until a quality measure is optimized.