1. A method, performed by computing functionality, for converting an input linguistic item into to a normalized linguistic item, the method executed by one or more processing devices of the computing functionality, the method comprising: receiving the input linguistic item; partitioning the input linguistic item into one or more tokens; expanding each of the tokens in the input linguistic item into a list of one or more candidate tokens, to provide an expanded linguistic item; creating a graph based on the expanded linguistic item; assigning weights to edges in the graph, using, at least in part, a statistical language model; and identifying a shortest path through the graph, to thereby identify a normalized linguistic item which represents a normalized counterpart of the input linguistic item.
1. A method, performed by computing functionality, for converting an input linguistic item into to a normalized linguistic item, the method executed by one or more processing devices of the computing functionality, the method comprising: receiving the input linguistic item; partitioning the input linguistic item into one or more tokens; expanding each of the tokens in the input linguistic item into a list of one or more candidate tokens, to provide an expanded linguistic item; creating a graph based on the expanded linguistic item; assigning weights to edges in the graph, using, at least in part, a statistical language model; and identifying a shortest path through the graph, to thereby identify a normalized linguistic item which represents a normalized counterpart of the input linguistic item. 6. The method of claim 1 , wherein the graph that is created constitutes an original graph, the method further comprising: adding a duplicate node to the original graph, wherein the duplicate node is a duplicate of an existing node in the original graph, said adding being performed to take account of two different paths that lead to the existing node, said adding being performing one or more times to generate a node-expanded graph.