Abstract: According to aspects of the disclosed subject matter, a taste graph comprising likely content collection nodes with corresponding likely digital content items is generated through one or more analyses of a corpus of content collections that is maintained by the online content service. As should be understood, this corpus of content collections is comprised of a plurality of curated content collections, with each content collection comprising a plurality of digital content items. With this taste graph available, as a user generates (or in response to a user generating) a content collection of digital content items, reference can be made to the taste graph to identify one or more digital content items that may be added to the content collection, where the one or more digital content items have a probabilistic likelihood of being complimentary and/or compatible with the other digital content items of the content collection.

Abstract: According to aspects of the disclosed subject matter, a taste graph comprising likely content collection nodes with corresponding likely digital content items is generated through one or more analyses of a corpus of content collections that is maintained by the online content service. As should be understood, this corpus of content collections is comprised of a plurality of curated content collections, with each content collection comprising a plurality of digital content items. With this taste graph available, as a user generates (or in response to a user generating) a content collection of digital content items, reference can be made to the taste graph to identify one or more digital content items that may be added to the content collection, where the one or more digital content items have a probabilistic likelihood of being complimentary and/or compatible with the other digital content items of the content collection.

Abstract: The described implementations are operable to determine potential objects of interest to a user based on a blend of the user's long-term behavior and short-term interests. Long term user behavior may be determined for the user over a period of time and represented as continuous data. Short-term interest may be determined based on objects with which the user has recently interacted, and attributes of those objects may be represented together as continuous data corresponding to the short-term user interest. The continuous data of the short-term user interest and long-term user behavior may be blended to produce a user embedding. The user embedding may then be compared with objects to determine objects that are of potential interest to the user.

Abstract: According to aspects of the disclosed subject matter, a taste graph comprising likely content collection nodes with corresponding likely digital content items is generated through one or more analyses of a corpus of content collections that is maintained by the online content service. As should be understood, this corpus of content collections is comprised of a plurality of curated content collections, with each content collection comprising a plurality of digital content items. With this taste graph available, as a user generates (or in response to a user generating) a content collection of digital content items, reference can be made to the taste graph to identify one or more digital content items that may be added to the content collection, where the one or more digital content items have a probabilistic likelihood of being complimentary and/or compatible with the other digital content items of the content collection.

Abstract: According to aspects of the disclosed subject matter, a taste graph comprising likely content collection nodes with corresponding likely digital content items is generated through one or more analyses of a corpus of content collections that is maintained by the online content service. As should be understood, this corpus of content collections is comprised of a plurality of curated content collections, with each content collection comprising a plurality of digital content items. With this taste graph available, as a user generates (or in response to a user generating) a content collection of digital content items, reference can be made to the taste graph to identify one or more digital content items that may be added to the content collection, where the one or more digital content items have a probabilistic likelihood of being complimentary and/or compatible with the other digital content items of the content collection.

Abstract: The described implementations are operable to determine potential objects of interest to a user based on a blend of the user's long-term behavior and short-term interests. Long term user behavior may be determined for the user over a period of time and represented as continuous data. Short-term interest may be determined based on objects with which the user has recently interacted, and attributes of those objects may be represented together as continuous data corresponding to the short-term user interest. The continuous data of the short-term user interest and long-term user behavior may be blended to produce a user embedding. The user embedding may then be compared with objects to determine objects that are of potential interest to the user.

Abstract: The described implementations are operable to determine potential objects of interest to a user based on a blend of the user's long-term behavior and short-term interests. Long term user behavior may be determined for the user over a period of time and represented as continuous data. Short-term interest may be determined based on objects with which the user has recently interacted and attributes of those objects may be represented together as continuous data corresponding to the short-term user interest. The continuous data of the short-term interest and long-term user behavior may be blended to produce a user embedding. The user embedding may then be compared with objects to determine objects that are of potential interest to the user.

Abstract: A system and method to facilitate matching of content to advertising information in a network are described. A request for advertising information is received over a network, the advertising information to be displayed for a user entity in association with content information within a web page requested by the user entity. Advertising information related to one or more themes of the content information on the web page is further determined, the themes representing subject matter contextually related to the content information. Advertisements are further selected from the advertising information based on keywords and metadata stored within the web page and based on a set of predetermined parameters stored within the data storage module. The selected advertisements are further ranked to obtain a ranked list of advertisements.

Abstract: A system and method to facilitate classification and storage of events in a network are described. An event and associated content information are received from an entity over a network. The content information is further analyzed to determine one or more themes representing subject matter related to the content information. The event is further classified according to the themes into one or more corresponding categories. Finally, the event is stored into one or more corresponding databases of a data storage module according to the one or more corresponding categories.

Abstract: A system and method to facilitate classification and storage of events in a network are described. An event and associated content information are received from an entity over a network. The content information is further analyzed to determine one or more themes representing subject matter related to the content information. The event is further classified according to the themes into one or more corresponding categories. Finally, the event is stored into one or more corresponding databases of a data storage module according to the one or more corresponding categories.

Abstract: A system and method to facilitate matching of content to advertising information in a network are described. A request for advertising information is received over a network, the advertising information to he displayed for a user entity in association with content information within a web page requested by the user entity. Advertising information related to one or more themes of the content information on the web page is further determined, the themes representing subject matter contextually related to the content information. Advertisements are further selected from the advertising information based on keywords and metadata stored within the web page and based on a set of predetermined parameters stored within the data storage module. The selected advertisements are further ranked to obtain a ranked list of advertisements.

Abstract: A system and method to facilitate mapping and storage of data within one or more data taxonomies are described. Content information is received over a network. The content information is further analyzed to determine at least one theme representing subject matter related to the content information. Finally, the content information is stored within respective predetermined categories organized within at least one taxonomy, the predetermined categories being associated with the at least one theme.