9. One or more computer-readable storage media according to claim 8 , wherein the machine learning based model training is executed.
8. One or more computer-readable storage media storing information to enable a computing device to perform a process, wherein the computer-readable storage media is not a signal, the process comprising: receiving a clickthrough log comprised of information indicating URLs that were clicked by users when presented in search results, the clickthrough log having been accumulated by a search engine that provided the search results to the users in response to queries from the users, the search engine having an existing index of web pages crawled from the Internet; receiving a list of candidate URLs, the candidate URLs comprising URLs being considered for inclusion in a new index of the web pages crawled from the Internet, each URL identifying a web page on the Internet; training a model and storing the model on the computing device, wherein the model is trained using training data comprised of URLs and information indicating whether the URLs were clicked in a search result of the search engine; selecting a URL from the list of candidate URLs, computing a feature vector of the selected URL by computing features of the URL that are included in the feature vector, the features including a click feature that is based on information from the clickthrough log that indicates whether or how often or how many times the selected URL has been clicked in search results of the search engine; passing the feature vector to the trained model and outputting, according to the trained model, a measure of how likely the selected URL is to be searched in the future by a user submitting a future unknown query to the search engine; using the measure to determine whether to include the selected URL in the new index; and building the new index and providing the new index to the search engine which uses the new index to answer user queries for web pages, wherein the search engine uses the new index by receiving a user query, searching the new index for web pages that match the user query, and when no web pages are found in the new index, using a second index that indexes web pages not indexed in the new index.