1. A method for indexing content items based on click-through features, the method comprising: generating a training set comprising one or more query-content item pairs, wherein a given query-content item pair has one or more click-through features associated therewith, the one or more click-through features including two or more of an average amount of time users stay on a website associated with a given URL, a spam score of the given URL, expected clicks at a position of the given URL in a given search results page and frequency of a query in a query log; labeling one or more query-content item pairs in the training set by assigning click score thereto based on the one or more click-through features thereof, wherein labeling a given content item in the training set comprises providing a given query-content item pair to a human judge to assign a click score; determining a click score function using a loss function based on the click scores of the labeled query-content item pairs and the click-through features thereof; applying the click score function to a plurality of unlabeled query-content item pairs to determine click scores thereof based on the one or more click-through features of the unlabeled query-content item pairs; generating an inverted click-through index of the unlabeled query-content item pairs and the associated query-score pairs, wherein a key to the index is a URL of the content item; and combining the inverted click-through index with a content index by associating the unlabeled query-content item pairs with content items in the content index.
1. A method for indexing content items based on click-through features, the method comprising: generating a training set comprising one or more query-content item pairs, wherein a given query-content item pair has one or more click-through features associated therewith, the one or more click-through features including two or more of an average amount of time users stay on a website associated with a given URL, a spam score of the given URL, expected clicks at a position of the given URL in a given search results page and frequency of a query in a query log; labeling one or more query-content item pairs in the training set by assigning click score thereto based on the one or more click-through features thereof, wherein labeling a given content item in the training set comprises providing a given query-content item pair to a human judge to assign a click score; determining a click score function using a loss function based on the click scores of the labeled query-content item pairs and the click-through features thereof; applying the click score function to a plurality of unlabeled query-content item pairs to determine click scores thereof based on the one or more click-through features of the unlabeled query-content item pairs; generating an inverted click-through index of the unlabeled query-content item pairs and the associated query-score pairs, wherein a key to the index is a URL of the content item; and combining the inverted click-through index with a content index by associating the unlabeled query-content item pairs with content items in the content index. 2. The method of claim 1 further comprising the step of identifying a content item using a Uniform Resource Locator (“URL”).