10. A method for detecting new topics in a plurality of interactions, given a plurality of known topics, 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 detected new fragments to an empty collection; computing, by the processor, a similarity between each fragment 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; identifying, by the processor, for each fragment, a corresponding topic having a highest similarity; adding, by the processor, a fragment of the fragments to the collection of detected new fragments in response to the similarity between the fragment and the corresponding topic having the highest similarity is less than a threshold value; extracting, by the processor, one or more new topics from the collection of detected new fragments; and returning, by the processor, a collection of the one or more new topics detected in the plurality of interactions, the collection comprising indications of frequencies at which the one or more new topics occur in the plurality of interactions during the particular time period.
10. A method for detecting new topics in a plurality of interactions, given a plurality of known topics, 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 detected new fragments to an empty collection; computing, by the processor, a similarity between each fragment 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; identifying, by the processor, for each fragment, a corresponding topic having a highest similarity; adding, by the processor, a fragment of the fragments to the collection of detected new fragments in response to the similarity between the fragment and the corresponding topic having the highest similarity is less than a threshold value; extracting, by the processor, one or more new topics from the collection of detected new fragments; and returning, by the processor, a collection of the one or more new topics detected in the plurality of interactions, the collection comprising indications of frequencies at which the one or more new topics occur in the plurality of interactions during the particular time period. 11. The method of claim 10 , further comprising: receiving, by the processor, a request to stop tracking a blacklisted topic; adding, by the processor, the blacklisted topic to a collection of blacklisted topics; and computing, by the processor, a similarity between each fragment and each of the blacklisted topics, wherein the computing, by the processor, the similarity between each fragment and each of the known topics is only performed in response to the similarity of the fragment to any blacklisted topic being less than a blacklist threshold value.