1. A computer-executed method comprising the steps of: creating a model by: receiving a data set that includes a plurality of words in a particular language, wherein in the particular language, words are formed by characters; wherein the plurality of words include items for which designated results have not been previously established; wherein an item is either a single character or a segment that comprises a plurality of characters; determining which items are related based on an analysis of the data set; based on the determining which items are related, generating, from items in the data set, clusters of related items; a computer system generating the model based at least on both: the clusters of related items; and training data that includes a plurality of entries, wherein each entry includes an entry item and a designated result for said entry item; wherein the step of generating the model comprises applying features to items in the training data based on the clusters of related items; after generating the model, performing the steps of: receiving a set of input data, wherein the input data includes items that have not been associated with designated results; and applying the model to the input data to determine predicted results for items within the input data.
17. One or more non-transitory computer readable storage media storing instructions which, when executed by one or more computing devices, cause performance of the method recited in claim 1 .