1. A computer-implemented method, the method comprising: obtaining a collection of phrases from at least one electronic resource; generating, from a collection of search queries, respective counts of each n-gram of terms that appears in search queries in the collection of search queries; determining, based at least in part on the collection of phrases and the respective counts of the n-grams, a respective segmentation for each search query in the collection of search queries, wherein the search query comprises a plurality of terms, and wherein the segmentation identifies at least one phrase using at least one term of the search query; storing, in a database of a service provider environment, the service provider environment including a plurality electronic resources available over a network, the respective segmentation for each search query in the collection of search queries to be used as training data for training a predictive model, wherein the training data includes a plurality of search queries in the collection of search queries as an input and the corresponding segmentation for the search queries as an output; and generating the predictive model using at least the training data, wherein the trained predictive model is configured to predict respective segmentations for new search queries.
1. A computer-implemented method, the method comprising: obtaining a collection of phrases from at least one electronic resource; generating, from a collection of search queries, respective counts of each n-gram of terms that appears in search queries in the collection of search queries; determining, based at least in part on the collection of phrases and the respective counts of the n-grams, a respective segmentation for each search query in the collection of search queries, wherein the search query comprises a plurality of terms, and wherein the segmentation identifies at least one phrase using at least one term of the search query; storing, in a database of a service provider environment, the service provider environment including a plurality electronic resources available over a network, the respective segmentation for each search query in the collection of search queries to be used as training data for training a predictive model, wherein the training data includes a plurality of search queries in the collection of search queries as an input and the corresponding segmentation for the search queries as an output; and generating the predictive model using at least the training data, wherein the trained predictive model is configured to predict respective segmentations for new search queries. 3. The computer-implemented method of claim 1 , further comprising: providing at least one different search query as an input to the predictive model, wherein the different search query comprises a plurality of terms; and receiving, from the predictive model, a predicted segmentation for the different search query, wherein the predicted segmentation identifies at least one phrase using at least one term of the different search query.