Abstract: Each image of a plurality of user-defined collections of images has properties associated therewith. A seed image is defined as currently viewed or selected image and the properties associated with the seed image are retrieved. The seed image is used to identify seed collections as the collections of images which have the seed image as one of their images. A plurality of candidate images are identified from the seed collections. For each candidate image, a significance score is determined as a function of either the number of seed collections to which the candidate image belongs or the ratio of the number of seed collections to the set of all collections to which the candidate image belongs. Each candidate image is ranked based on the significance scores and the seed image properties. At least one candidate image is recommended to the user based on the ranking of the candidate images.

Abstract: Each image of a plurality of user-defined collections of images has properties associated therewith. A seed image is defined as currently viewed or selected image and the properties associated with the seed image are retrieved. The seed image is used to identify seed collections as the collections of images which have the seed image as one of their images. A plurality of candidate images are identified from the seed collections. For each candidate image, a significance score is determined as a function of either the number of seed collections to which the candidate image belongs or the ratio of the number of seed collections to the set of all collections to which the candidate image belongs. Each candidate image is ranked based on the significance scores and the seed image properties. At least one candidate image is recommended to the user based on the ranking of the candidate images.

Abstract: A method of selecting content object tags for recommendation to a user includes having a taxonomy of tags, with a plurality of tag taxonomy branches, for labeling content objects to be stored at a content hosting service; identifying a baseline subset of content objects based on a user context at the content hosting service; identifying a targeted subset of the baseline subset of content objects based on the user context, wherein each content object in the targeted subset of content objects is associated with one or more tags; determining a tag score for each tag associated with the targeted subset of content objects; determining a maximum number of tags to be recommended to the user based on available space within a user interface of the user; selecting tags with the highest recommendation score from a number of different tag taxonomy branches, as recommended tags to the user, the number being no more than the maximum number; receiving tags selected by the user from among the recommended tags; and performing

Abstract: A method of selecting content object tags for recommendation to a user includes having a taxonomy of tags for labeling content objects to be stored at a content hosting service; identifying a baseline subset of content objects based on a user context at the content hosting service; identifying a targeted subset of the baseline subset based on the user context; determining a tag score for each tag associated with the targeted subset of content objects; determining a maximum number of tags to be recommended to the user based on available space within a user interface of the user; selecting tags with the highest recommendation score from a number of different tag taxonomy branches, the number being no more than the maximum number; receiving tags selected by the user from among the recommended tags; and performing an operation on the content object corpus for the user context using the selected tags.

Abstract: Each image of a plurality of user-defined collections of images has properties associated therewith. A seed image is defined as currently viewed or selected image and the properties associated with the seed image are retrieved. The seed image is used to identify seed collections as the collections of images which have the seed image as one of their images. A plurality of candidate images are identified from the seed collections. For each candidate image, a significance score is determined as a function of either the number of seed collections to which the candidate image belongs or the ratio of the number of seed collections to the set of all collections to which the candidate image belongs. Each candidate image is ranked based on the significance scores and the seed image properties. At least one candidate image is recommended to the user based on the ranking of the candidate images.

Abstract: Collections identifying associated content objects, such as user-defined collections, are stored. A request to display or play a seed content object is received. A plurality of seed collections are identified based on the seed object. A plurality of candidate content objects are identified based on the identified seed collections, for instance by identifying the content objects that are identified by the seed collections. Properties of the seed object are identified, such as the categorization of the seed object, or the tags associated with the seed object. The candidate objects are ranked based on the identified seed collections and the identified properties of the seed object, and a candidate object is selected for recommendation to the user based on the ranking. The ranking of candidate objects can also be determined based on the coherence of the seed collections and the centrality of the seed object to the seed collections.

Abstract: A method of selecting content object tags for recommendation to a user includes having a taxonomy of tags, with a plurality of tag taxonomy branches, for labeling content objects to be stored at a content hosting service; identifying a baseline subset of content objects based on a user context at the content hosting service; identifying a targeted subset of the baseline subset of content objects based on the user context, wherein each content object in the targeted subset of content objects is associated with one or more tags; determining a tag score for each tag associated with the targeted subset of content objects; determining a maximum number of tags to be recommended to the user based on available space within a user interface of the user; selecting tags with the highest recommendation score from a number of different tag taxonomy branches, as recommended tags to the user, the number being no more than the maximum number; receiving tags selected by the user from among the recommended tags; and performing

Abstract: Content object tags at a content hosting service are used to classify stored content objects. Tags and clusters of tags (groups of one or more associated tags) can be recommended to a user of the content hosting service based on a user context, such as the browsing, viewing, uploading, or searching of content objects. Tags are scored based on content objects tagged with the tags in a targeted subset of content objects and a baseline subset of content objects, and based on the relevance of the content objects tagged with the tags. These tag scores can be weighted, and one or more tags can be selected for recommendation based on the weighted tag scores. Tag clusters can be selected for recommendation using a cluster hierarchy and determining whether a targeted subset of tags occur within a maximum number of tag clusters at a particular hierarchy level.

Abstract: Content object tags at a content hosting service are used to classify stored content objects. Tags and clusters of tags (groups of one or more associated tags) can be recommended to a user of the content hosting service based on a user context, such as the browsing, viewing, uploading, or searching of content objects. Tags are scored based on content objects tagged with the tags in a targeted subset of content objects and a baseline subset of content objects, and based on the relevance of the content objects tagged with the tags. These tag scores can be weighted, and one or more tags can be selected for recommendation based on the weighted tag scores. Tag clusters can be selected for recommendation using a cluster hierarchy and determining whether a targeted subset of tags occur within a maximum number of tag clusters at a particular hierarchy level.

Abstract: Collections identifying associated content objects, such as user-defined collections, are stored. A request to display or play a seed content object is received. A plurality of seed collections are identified based on the seed object. A plurality of candidate content objects are identified based on the identified seed collections, for instance by identifying the content objects that are identified by the seed collections. Properties of the seed object are identified, such as the categorization of the seed object, or the tags associated with the seed object. The candidate objects are ranked based on the identified seed collections and the identified properties of the seed object, and a candidate object is selected for recommendation to the user based on the ranking. The ranking of candidate objects can also be determined based on the coherence of the seed collections and the centrality of the seed object to the seed collections.

Abstract: Collections identifying associated content objects, such as user-defined collections, are stored. A request to display or play a seed content object is received. A plurality of seed collections are identified based on the seed object. A plurality of candidate content objects are identified based on the identified seed collections, for instance by identifying the content objects that are identified by the seed collections. Properties of the seed object are identified, such as the categorization of the seed object, or the tags associated with the seed object. The candidate objects are ranked based on the identified seed collections and the identified properties of the seed object, and a candidate object is selected for recommendation to the user based on the ranking. The ranking of candidate objects can also be determined based on the coherence of the seed collections and the centrality of the seed object to the seed collections.

Abstract: Content object tags at a content hosting service are used to classify stored content objects. Tags and clusters of tags (groups of one or more associated tags) can be recommended to a user of the content hosting service based on a user context, such as the browsing, viewing, uploading, or searching of content objects. Tags are scored based on content objects tagged with the tags in a targeted subset of content objects and a baseline subset of content objects, and based on the relevance of the content objects tagged with the tags. These tag scores can be weighted, and one or more tags can be selected for recommendation based on the weighted tag scores. Tag clusters can be selected for recommendation using a cluster hierarchy and determining whether a targeted subset of tags occur within a maximum number of tag clusters at a particular hierarchy level.

Abstract: Content object tags at a content hosting service are used to classify stored content objects. Tags and clusters of tags (groups of one or more associated tags) can be recommended to a user of the content hosting service based on a user context, such as the browsing, viewing, uploading, or searching of content objects. Tags are scored based on content objects tagged with the tags in a targeted subset of content objects and a baseline subset of content objects, and based on the relevance of the content objects tagged with the tags. These tag scores can be weighted, and one or more tags can be selected for recommendation based on the weighted tag scores. Tag clusters can be selected for recommendation using a cluster hierarchy and determining whether a targeted subset of tags occur within a maximum number of tag clusters at a particular hierarchy level.