1. A method comprising: providing, on a user interface associated with an apparatus, a presentation of a menu of one or more topics from among a predetermined hierarchy of topics and subtopics to a user; receiving, via the user interface by the apparatus, a first input from the user specifying at least one of the one or more topics from among the predetermined hierarchy of topics and subtopics; retrieving, by the apparatus, one or more documents associated with the user; extracting, by the apparatus, noun tokens from the documents based, at least in part, on the specified topics; performing, by the apparatus, histogram processing of the extracted noun tokens to provide a list of pertinent tokens; comparing, by the apparatus, topic input information received from the user with the list of pertinent tokens to determine if there is a corresponding match; generating, by the apparatus, a topology of the matching tokens according to a probabilistic model, wherein the topology matches the matching pertinent tokens with the topics and subtopics of the hierarchy; providing, on the user interface by the apparatus, a presentation of top-level topics as topic icons on a tool bar on the user interface based, at least in part, on the topology of matching tokens; and in response to a second input from the user specifying one of the topic icons, providing, on the user interface by the apparatus, a presentation of one or more search results customized for the user using machine learning based on the topology.
1. A method comprising: providing, on a user interface associated with an apparatus, a presentation of a menu of one or more topics from among a predetermined hierarchy of topics and subtopics to a user; receiving, via the user interface by the apparatus, a first input from the user specifying at least one of the one or more topics from among the predetermined hierarchy of topics and subtopics; retrieving, by the apparatus, one or more documents associated with the user; extracting, by the apparatus, noun tokens from the documents based, at least in part, on the specified topics; performing, by the apparatus, histogram processing of the extracted noun tokens to provide a list of pertinent tokens; comparing, by the apparatus, topic input information received from the user with the list of pertinent tokens to determine if there is a corresponding match; generating, by the apparatus, a topology of the matching tokens according to a probabilistic model, wherein the topology matches the matching pertinent tokens with the topics and subtopics of the hierarchy; providing, on the user interface by the apparatus, a presentation of top-level topics as topic icons on a tool bar on the user interface based, at least in part, on the topology of matching tokens; and in response to a second input from the user specifying one of the topic icons, providing, on the user interface by the apparatus, a presentation of one or more search results customized for the user using machine learning based on the topology. 2. A method of claim 1 , wherein the extracting of the noun tokens comprises: identifying substantially all noun tokens in the documents; selecting one of the identified noun tokens based, at least in part, on whether the one identified noun token is semantically related to the specified topics, wherein the extracted noun tokens include the selected one identified noun token; providing, on the user interface by the apparatus, a presentation of topics determined based on the topology; and receiving, via the user interface by the apparatus, a third input from the user specifying a subset of the topics, wherein the topic icons correspond to the subset of the topics.