1. A computer-implemented method for user query reformulation, the method comprising: creating, using a processor, a graph that represents a relationship between previous user query terms, the graph comprising nodes that represent the previous user query terms, each of the nodes comprising an n-gram, and edges connecting the nodes; wherein creating the graph comprises performing a random walk analysis to quantify relationships between nodes of the graph, wherein performing the random walk analysis comprises: generating parallel corpora of paired phrases based on a plurality of different fields comprising a plurality of content fields and one or more a popularity fields such that a plurality of edge types occur between at least two nodes; extracting a plurality of aligned n-grams based on alignment probabilities between different n-grams; generating the edges between the aligned n-grams based on the alignment probability of each corresponding edge type; and determining whether to reformulate a user query based on a relationship between a user search term in the user query and a graphed search term represented by a node of the graph taking into account a relationship between the user search term and the graphed search term.
1. A computer-implemented method for user query reformulation, the method comprising: creating, using a processor, a graph that represents a relationship between previous user query terms, the graph comprising nodes that represent the previous user query terms, each of the nodes comprising an n-gram, and edges connecting the nodes; wherein creating the graph comprises performing a random walk analysis to quantify relationships between nodes of the graph, wherein performing the random walk analysis comprises: generating parallel corpora of paired phrases based on a plurality of different fields comprising a plurality of content fields and one or more a popularity fields such that a plurality of edge types occur between at least two nodes; extracting a plurality of aligned n-grams based on alignment probabilities between different n-grams; generating the edges between the aligned n-grams based on the alignment probability of each corresponding edge type; and determining whether to reformulate a user query based on a relationship between a user search term in the user query and a graphed search term represented by a node of the graph taking into account a relationship between the user search term and the graphed search term. 8. The computer-implemented method recited in claim 1 , comprising reformulating the user query using expansion.