1. A system comprising: a machine having a memory and at least one processor, the memory storing a set of instructions that, in response to execution by at least one processor, causes the system to perform operations comprising; receiving a plurality of clickstreams, each clickstream of the plurality of clickstreams being formatted as a first-order Markov chain model and representing a sequence of user actions during interaction with a website; iteratively training a self-organizing map (SOM) framework to obtain input data that is representative of the clickstreams formatted as the Markov chain model, the training including collecting a list of clickstreams of the plurality of clickstreams that match each of the vector prototypes of the SOM framework, adjusting the vector prototypes using the collection of clickstreams in the list of clickstreams, applying an expectation-maximization (EM) algorithm to search a domain of model parameters and update the Markov chain models across grid points of the SOM, and decreasing a size of a neighborhood around the vector prototypes in each iteration; mapping the clickstream to a two-dimensional map, the mapping including projecting the input data into a two-dimensional space; receiving the mapped clickstream; creating a visual representation of each clickstream to be displayed on a device, wherein: each visual representation comprises a distinct graphical element for each of the user actions of the corresponding clickstream and an attribute that is configured to indicate a frequency level of the corresponding clickstream, and the visual representation is created based on a probability model; receiving an indication of a selection of one of the visual representations; and causing additional information about the clickstream corresponding to the one of the visual representations to be displayed on the device, the additional information being related to user interaction with the website as indicated by the clickstream upon which an update to the website is based.