Google Inc.

Anna Majkowska

Cristian Tapus

Yun Zhou

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for query categorization based on image results. In one aspect, a method includes receiving images from image results responsive to a query, wherein each of the images is associated with an order in the image results and respective user behavior data for the image as a search result for the first query, and associating one or more of the first images with a plurality of annotations based on analysis of the selected first images' content.

Query categorization based on image results

A server device may receive first label information regarding a first cluster that includes information identifying a first set of documents, where the first label information regarding the first cluster includes a first set of labels that are associated with the first cluster, and second label information regarding a second cluster that includes information identifying a second set of documents, where the second label information regarding the second cluster includes a second set of labels that are associated with the second cluster, where the second set of documents is different from the first set of documents. The server device may determine that the first and second clusters are semantically similar, which may include determining whether a similarity of the first and second clusters is above a similarity threshold.

Merging semantically similar clusters based on cluster labels

One or more server devices may receive first navigation information identifying a first set of documents that are selected after a first document is presented and second navigation information identifying a second set of documents that are selected after a second document is presented; compare the first set of documents to the second set of documents; generate a similarity score based on the comparing; determine based on the similarity score, that the first document is similar to the second document; and generate, based on determining that the first document is similar to the second document, a cluster that includes identification information identifying the first document and the second document.

Clustering documents based on common document selections

A server device may receive first label information regarding a first cluster that includes information identifying a first set of documents, where the first label information regarding the first cluster includes a first set of labels that are associated with the first cluster, and second label information regarding a second cluster that includes information identifying a second set of documents, where the second label information regarding the second cluster includes a second set of labels that are associated with the second cluster, where the second set of documents is different from the first set of documents. The server device may also form a merged cluster by merging the first and second clusters. The server device may further determine one or more labels for the merged cluster. Furthermore, the server device may assign the one or more labels to the merged cluster.

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San Francisco, CA, United States of America

Anna Majkowska