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. 12. The method of claim 10 , further comprising: receiving, by the processor, a request to start tracking a user topic; adding, by the processor, the user topic to a collection of user topics; determining, by the processor, whether one or more of the user topics are user suggested topics; generating, by the processor, a topic for each of the user suggested topics; and adding the collection of user topics to the plurality of known topics.