1. A method for tracking known topics in a plurality of interactions, the method comprising: extracting, by a processor, a plurality of fragments from the plurality of interactions, the plurality of interactions occurring over a particular time period, each fragment of the plurality of fragments comprising one or more words; initializing, by the processor, a collection of tracked topics to an empty collection; computing, by the processor, a similarity between each fragment of the fragments and each of the known topics, each of the known topics comprising a template fragment comprising one or more template words, the similarity between a fragment of the fragments and a topic of the known topics being computed based on the one or more words of the fragment and the one or more template words of the template fragment of the topic; adding, by the processor, a known topic of the known topics to the tracked topics in response to the similarity between a fragment and the known topic exceeding a threshold value; and returning, by the processor, a collection of the tracked topics detected in the plurality of interactions, the collection comprising indications of frequencies at which the tracked topics occur in the plurality of interactions during the particular time period.
1. A method for tracking known topics in a plurality of interactions, the method comprising: extracting, by a processor, a plurality of fragments from the plurality of interactions, the plurality of interactions occurring over a particular time period, each fragment of the plurality of fragments comprising one or more words; initializing, by the processor, a collection of tracked topics to an empty collection; computing, by the processor, a similarity between each fragment of the fragments and each of the known topics, each of the known topics comprising a template fragment comprising one or more template words, the similarity between a fragment of the fragments and a topic of the known topics being computed based on the one or more words of the fragment and the one or more template words of the template fragment of the topic; adding, by the processor, a known topic of the known topics to the tracked topics in response to the similarity between a fragment and the known topic exceeding a threshold value; and returning, by the processor, a collection of the tracked topics detected in the plurality of interactions, the collection comprising indications of frequencies at which the tracked topics occur in the plurality of interactions during the particular time period. 4. The method of claim 1 , wherein the plurality of interactions correspond to a first time period comprising the particular time period, and wherein the method further comprises: extracting, by a processor, a second plurality of fragments from a second plurality of interactions, the second plurality of interactions corresponding to a second time period, the second time period being different from the first time period; initializing, by the processor, a second collection of tracked topics to the empty collection; computing, by the processor, a similarity between each fragment of the second fragments and each of the known topics; and adding, by the processor, a known topic of the known topics to the second tracked topics in response to the similarity between a fragment and the known topic exceeding the threshold value.