1. A computing system with a central processing unit and memory for projecting images and queries into a similarity space, comprising: a data store that provides queries and images as training data and relevance of the images to the queries, the queries and images having associated words, the words being from a collection of words; a relevance extraction component that, for each image, identifies an image relevance for the most relevant words to the image, the image relevance represented by a most-relevant image feature having non-zero scores for each of the words of the collection that are most relevant to the image and having a score of zero for each of the other words of the collection; and for each query, identifies a query relevance for the most relevant words to the query, the query relevance represented by a most-relevant query feature having non-zero scores for each of the words of the collection that are most relevant to the query and a score of zero for each of the other words of the collection; and for each image, identifies a query-specific image relevance that is specific to the query, the query-specific image relevance represented by a query-specific image feature having scores indicating relevance of the image to each of those most relevant words of the query and having scores of zero for each of the other words of the collection, the query-specific image feature being generated by: for each of the most-relevant words to the query as indicated by a non-zero score in the most-relevant query feature, extracting the score for that most-relevant word from the most-relevant image feature for the image; and setting the score for that most-relevant word in the query-specific image feature to the extracted score; and setting the score for the other words of the query-specific image feature to zero; so that each combination of a query and an image has a query-specific image feature that includes, for each of the most relevant words of the query, the relevance score for that most relevant word from the image feature; a learn projection component that learns a projection of the most-relevant query features to a similarity space and a projection of the query-specific image features to the similarity space so that in the similarity space distances between queries and their relevant images are smaller than distances between queries and their non-relevant images; and a search component that identifies the most relevant words of a target query and their query relevance to the target query represented by a most-relevant query feature; for each image, identifies image relevance to the image of the identified most-relevant words represented by a query-specific image feature; projects the most-relevant query feature and the query-specific image feature; and selects images with projected query-specific image features whose distances from the projected most-relevant query feature in the similarity space are smallest as being relevant to the query.
1. A computing system with a central processing unit and memory for projecting images and queries into a similarity space, comprising: a data store that provides queries and images as training data and relevance of the images to the queries, the queries and images having associated words, the words being from a collection of words; a relevance extraction component that, for each image, identifies an image relevance for the most relevant words to the image, the image relevance represented by a most-relevant image feature having non-zero scores for each of the words of the collection that are most relevant to the image and having a score of zero for each of the other words of the collection; and for each query, identifies a query relevance for the most relevant words to the query, the query relevance represented by a most-relevant query feature having non-zero scores for each of the words of the collection that are most relevant to the query and a score of zero for each of the other words of the collection; and for each image, identifies a query-specific image relevance that is specific to the query, the query-specific image relevance represented by a query-specific image feature having scores indicating relevance of the image to each of those most relevant words of the query and having scores of zero for each of the other words of the collection, the query-specific image feature being generated by: for each of the most-relevant words to the query as indicated by a non-zero score in the most-relevant query feature, extracting the score for that most-relevant word from the most-relevant image feature for the image; and setting the score for that most-relevant word in the query-specific image feature to the extracted score; and setting the score for the other words of the query-specific image feature to zero; so that each combination of a query and an image has a query-specific image feature that includes, for each of the most relevant words of the query, the relevance score for that most relevant word from the image feature; a learn projection component that learns a projection of the most-relevant query features to a similarity space and a projection of the query-specific image features to the similarity space so that in the similarity space distances between queries and their relevant images are smaller than distances between queries and their non-relevant images; and a search component that identifies the most relevant words of a target query and their query relevance to the target query represented by a most-relevant query feature; for each image, identifies image relevance to the image of the identified most-relevant words represented by a query-specific image feature; projects the most-relevant query feature and the query-specific image feature; and selects images with projected query-specific image features whose distances from the projected most-relevant query feature in the similarity space are smallest as being relevant to the query. 5. The system of claim 1 including an annotation component that provides the image relevance of a target image to words; for each query, identifies the image relevance of the most relevant words to the target image; projects the image relevance of the target image into the similarity space; and selects queries that are close to the image as being relevant to the target image.