7. A system of one or more processing devices for indexing and searching content items based on its one or more click-through features, the system comprising: an index component, executed on the one or more processing devices, operative to determine a click score function using a loss function based on a training set of labeled query-content item pairs and the click-through features thereof, 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, wherein the training set of labeled query-content items comprises a plurality of query-content items having click scores assigned thereto by a human judge, assign click scores to a plurality of unlabeled query-content item pairs through application of the click score function to the one or more click-through features, generate an inverted click-through index of the unlabeled content items and the associated query-score pairs and combine the inverted click-through index with a content index by associating the unlabeled query-content item pairs with content items in the content index; a relevance engine, executed on the one or more processing devices, operative to receive one or more query scores for one or more content items and generate one or more relevance scores therefore; and a search engine, executed on the one or more processing devices, operative to retrieve one or more content items in a result set in response to receipt of the query from the user and order the content items in the result set according to the relevance scores from the relevance engine.
7. A system of one or more processing devices for indexing and searching content items based on its one or more click-through features, the system comprising: an index component, executed on the one or more processing devices, operative to determine a click score function using a loss function based on a training set of labeled query-content item pairs and the click-through features thereof, 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, wherein the training set of labeled query-content items comprises a plurality of query-content items having click scores assigned thereto by a human judge, assign click scores to a plurality of unlabeled query-content item pairs through application of the click score function to the one or more click-through features, generate an inverted click-through index of the unlabeled content items and the associated query-score pairs and combine the inverted click-through index with a content index by associating the unlabeled query-content item pairs with content items in the content index; a relevance engine, executed on the one or more processing devices, operative to receive one or more query scores for one or more content items and generate one or more relevance scores therefore; and a search engine, executed on the one or more processing devices, operative to retrieve one or more content items in a result set in response to receipt of the query from the user and order the content items in the result set according to the relevance scores from the relevance engine. 9. The system of claim 7 wherein the click score function is determined by minimizing difference between click score for the given query-content item pair in the training set and the output of the click score function.