Abstract: Methods, systems and apparatus for identifying result images for a query image. One or more labels that are associated with the query image are obtained. Candidate images matching the query labels are identified. Visual similarity scores are generated for the candidate images. Each visual similarity score represents the visual similarity of a respective candidate image to the query image. Relevance scores are generated for each of the candidate images based on the visual similarity scores. Each relevance score represents a measure of relevance of the respective candidate images to the query image. The candidate images are ranked based on the relevance scores, a highest ranking subset of the candidate images being identified as result images and referenced by image search results. The result images can be candidate images that satisfy a similarity condition relative to the query image and other result images.

Abstract: A system identifies an image and determines whether the image contains inappropriate content based on first data associated with the image, second data associated with a document that contains the image or refers to the image, and/or third data associated with a group of documents with which the image is associated.

Abstract: Image galleries are automatically located within documents, such as web pages. Documents that are determined to contain image galleries may be treated differently when storing the document for later retrieval by an image search engine. In one implementation, the image galleries are automatically located within a document by calculating position information indicating relative positions of images in the document. The document may be determined to contain an image gallery when the position information indicates that the images in the document are generally evenly distributed.

Abstract: Methods, systems and apparatus, including computer programs encoded on a computer storage medium, for determining similar queries for image searches. In one aspect, a method includes generating, for each of a plurality of search queries, a selection vector for the search query, each selection vector including a plurality of vector elements, each vector element corresponding to a unique image, and the value of each vector element being proportional to a number of selections of its corresponding unique image in response to the unique image being presented as a search result for the search query. The method further includes selecting a first search query and a second search query from the plurality of search queries and determining, from the selection vectors for the first and second search queries, a similarity measure that is a measurement of the similarity of the first search query to the second query.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for selecting labels for a non-text content item. In one aspect, a method receives a set of initial labels for a non-text content item, wherein the set of initial labels specifies text that has been identified as descriptive of the non-text content item and a web page to which the text corresponds. Initial labels corresponding to sets of matching web pages are grouped into separate initial label groups that correspond to each set of matching web pages. Sets of matching labels are grouped into other separate initial label groups that correspond to the sets of matching labels. One or more words that are included in at least a threshold number of the separate label groups are selected as final labels for the non-text content item.

Abstract: A method of processing documents is described. The method includes the operation of receiving a document in a search engine crawler. The document includes an embedded first link tag. The first link tag includes one or more information pairs. A respective information pair includes a respective parameter and a corresponding value. The parameters in the one or more information pairs may correspond to content at one or more content locations or one or more document locations. The method also includes selecting a method of processing content associated with the first link tag in accordance with one or more of the information pairs.

Abstract: A system identifies an image and determines whether the image contains inappropriate content based on first data associated with the image, second data associated with a document that contains the image or refers to the image, and/or third data associated with a group of documents with which the image is associated.

Abstract: A geographic relevance component determines geographic relevance of web resources based on an analysis of data points that correspond to estimated physical locations of the IP addresses of a number of visitors to the web site. The geographic relevance component may additionally determine the probability that a particular user is within the geographical relevance corresponding to a web resource.

Abstract: A method of processing documents is described. The method includes the operation of receiving a document in a search engine crawler. The document includes an embedded first link tag. The first link tag includes one or more information pairs. A respective information pair includes a respective parameter and a corresponding value. The parameters in the one or more information pairs may correspond to content at one or more content locations or one or more document locations. The method also includes selecting a method of processing content associated with the first link tag in accordance with one or more of the information pairs.

Abstract: A method of processing documents is described. The method includes the operation of receiving a document in a search engine crawler. The document includes an embedded first link tag. The first link tag includes one or more information pairs. A respective information pair includes a respective parameter and a corresponding value. The parameters in the one or more information pairs may correspond to content at one or more content locations or one or more document locations. The method also includes selecting a method of processing content associated with the first link tag in accordance with one or more of the information pairs.

Abstract: A system identifies an image and determines whether the image contains inappropriate content based on first data associated with the image, second data associated with a document that contains the image or refers to the image, and/or third data associated with a group of documents with which the image is associated.

Abstract: Image galleries are automatically located within documents, such as web pages. Documents that are determined to contain image galleries may be treated differently when storing the document for later retrieval by an image search engine. In one implementation, the image galleries are automatically located within a document by calculating position information indicating relative positions of images in the document. The document may be determined to contain an image gallery when the position information indicates that the images in the document are generally evenly distributed.

Abstract: A category classification component locates appropriate categories that apply to a user search query. The categories may be yellow page business listings. The category classification component may include a category model that is automatically trained on one or more of a number of possible training data sources. The training data sources may include directory listings, web documents, query traffic, and advertisement traffic.

Abstract: A system identifies an image and determines whether the image contains inappropriate content based on first data associated with the image, second data associated with a document that contains the image or refers to the image, and/or third data associated with a group of documents with which the image is associated.

Abstract: Systems and methods for assisted network browsing are described. In one described method, a client device receives an interest signal indicating a user's interest in a hyperlink contained in a first document. The client device responds to the interest signal by generating a request signal comprising a request for third-party-provided information about a second document associated with the hyperlink. The client device receives the requested third-party-provided information and causes it to be output in association with the first document.

Abstract: A category classification component locates appropriate categories that apply to a user search query. The categories may be yellow page business listings. The category classification component may include a category model that is automatically trained on one or more of a number of possible training data sources. The training data sources may include directory listings, web documents, query traffic, and advertisement traffic.