1. A computer-implemented method comprising: defining, using a definition module executable by a processor, a plurality of seed queries, each of the plurality seed queries corresponding to a query and associated with a task to be accomplished; summarizing the plurality of seed queries into one or more query patterns based, at least in part, on the task to be accomplished associated with each of the plurality of seed queries, wherein each of the one or more query patterns is associated with a query pattern task to be accomplished; determining a training data set comprising at least the plurality of seed queries and the query patterns; creating a graph comprising the one or more query patterns connected to one or more uniform resource locators (URLs) by one or more weighted edges; traversing the graph using a random walk algorithm to expand the training data set, wherein the random walk algorithm determines a plurality of transition probabilities such that each of the plurality of transition probabilities associates a query pattern of the one or more query patterns to a URL of the one or more URLs; and classifying the expanded training data set into one or more search task categories, wherein each of the one or more search task categories is associated with a classified task to be accomplished based, at least in part, on the query pattern task associated with an associated query pattern.