Abstract: In accordance with an embodiment, described herein is a system and method for delivery of content based on matching of user profiles with content metadata. The system enables delivery of personalized content, without the overhead of managing segment targeting rules, while providing content publishers or marketers with complete control over such personalization. A recommendation service or application program interface, provided by a computer, cloud computing environment, or other type of computer system, enables receipt and processing of requests, from client devices, for personalized content. A recommendation engine delivers content assets in response to a request from a client device. The recommendation engine determines a content channel and a user identity associated with the request, and then delivers content assets based on rules governing the matching of content asset metadata with the user profile. While content classification evolves over time, so also does the personalization of delivered content.

Abstract: Described herein are systems and methods automatic selection for dynamic site compilation in a cloud-based content hub environment. In accordance with an embodiment, embodiments provide an artificial intelligence/machine learning (AI/ML) engine that monitors and collects both content and consumption analytics associated with content items on a webpage. Based upon an analysis of such metrics, content can be automatically tagged such that the content item can be statically compiled with the website (optimized for viewing speed and user experience), or dynamically fetched/loaded on a load or refresh of the website.

Abstract: In accordance with an embodiment, described herein is a system and method for generation of starter websites. A content management system (CMS), such as for example, an Oracle Content and Experience Cloud (CEC) environment, can be provided. The content management system can include a site generator within the CMS. The site generator can receive a selection of content managed by the CMS, wherein the content includes data associated with the content. The site generator can determine, based on the data associated with the content, a layout of the content on a document. The site generator can generate machine readable code that, when interpreted or executed by a machine, causes the machine to produce a document including the content wherein the content is displayed in the determined layout.

Abstract: Described herein are systems and methods for providing custom component compilation within a cloud-based content hub environment. In accordance with an embodiment, embodiments can allow developers to work with a variety of technologies and optimize a page or site for runtime performance, including in some instances the use of a custom (component) compiler, for use during compilation of a particular component of a website.

Abstract: In accordance with an embodiment, described herein is a system and method for management and delivery of shoppable content data. A modeled content architecture can be provided within a content management system (CMS), such as for example, an Oracle Content and Experience Cloud (CEC) environment. The modeled content architecture can include document-type objects that represent a type of document, and field objects that represent a type of field that can be added to a document. The document-type objects and field objects can include attributes that describe the objects. An admin API operates as a contract between the CMS and a commerce provider system, for example an online retailer, and facilitates communication and data exchange between the CMS and the commerce provider.

Abstract: Described herein are systems and methods automatic selection for dynamic site compilation in a cloud-based content hub environment. In accordance with an embodiment, embodiments provide an artificial intelligence/machine learning (AI/ML) engine that monitors and collects both content and consumption analytics associated with content items on a webpage. Based upon an analysis of such metrics, content can be automatically tagged such that the content item can be statically compiled with the website (optimized for viewing speed and user experience), or dynamically fetched/loaded on a load or refresh of the website.

Abstract: Described herein are systems and methods for providing a correlated content organization in a content management system based upon a training set. In accordance with an embodiment, the systems and methods described herein can build a training set based upon observations of received inputs to determine patterns that are used often in content merges. Once a pattern is established, the systems and methods can provide indications of proposed merges based upon the training set and rules established therefrom that fit the same, or similar (e.g., within a defined variant) of the pattern. The system can then receive an indication of whether the suggestion is accepted or rejected, and such decision can be fed back into the learning system. This way the accuracy of the content merge improves over time.

Abstract: In accordance with an embodiment, described herein is a system and method for delivery of content based on matching of user profiles with content metadata. The system enables delivery of personalized content, without the overhead of managing segment targeting rules, while providing content publishers or marketers with complete control over such personalization. A recommendation service or application program interface, provided by a computer, cloud computing environment, or other type of computer system, enables receipt and processing of requests, from client devices, for personalized content. A recommendation engine delivers content assets in response to a request from a client device. The recommendation engine determines a content channel and a user identity associated with the request, and then delivers content assets based on rules governing the matching of content asset metadata with the user profile. While content classification evolves over time, so also does the personalization of delivered content.

Abstract: Described herein are systems and methods for providing a correlated content organization in a content management system based upon a training set. In accordance with an embodiment, the systems and methods described herein can build a training set based upon observations of received inputs to determine patterns that are used often in content merges. Once a pattern is established, the systems and methods can provide indications of proposed merges based upon the training set and rules established therefrom that fit the same, or similar (e.g., within a defined variant) of the pattern. The system can then receive an indication of whether the suggestion is accepted or rejected, and such decision can be fed back into the learning system. This way the accuracy of the content merge improves over time.

Abstract: Described herein are systems and methods automatic selection for dynamic site compilation in a cloud-based content hub environment. In accordance with an embodiment, embodiments provide an artificial intelligence/machine learning (AI/ML) engine that monitors and collects both content and consumption analytics associated with content items on a webpage. Based upon an analysis of such metrics, content can be automatically tagged such that the content item can be statically compiled with the website (optimized for viewing speed and user experience), or dynamically fetched/loaded on a load or refresh of the website.

Abstract: In accordance with an embodiment, described herein is a system and method for delivery of content based on matching of user profiles with content metadata. The system enables delivery of personalized content, without the overhead of managing segment targeting rules, while providing content publishers or marketers with complete control over such personalization. A recommendation service or application program interface, provided by a computer, cloud computing environment, or other type of computer system, enables receipt and processing of requests, from client devices, for personalized content. A recommendation engine delivers content assets in response to a request from a client device. The recommendation engine determines a content channel and a user identity associated with the request, and then delivers content assets based on rules governing the matching of content asset metadata with the user profile. While content classification evolves over time, so also does the personalization of delivered content.

Abstract: In accordance with an embodiment, systems and methods described herein can be used, for example with a content management system, to provide recommendations to categorize/classify content into user-defined categories, which in turn provides an opportunity for content managers to place new content into accurate categories effortlessly, based on previously evaluated/categorized content. A recommendation system or tool can use artificial intelligence (AI) techniques to continuously learn from past data, and assist in placing content into a relevant category through automatic categorization/classification of newly created/edited content. The recommendation tool can be implemented and applied across diverse domains by generating feature vectors from contents, creating clusters in the feature space based on previously categorized content, and recommending a category for new content through feature space distance calculation from the clusters.

Abstract: Described herein are systems and methods automatic selection for dynamic site compilation in a cloud-based content hub environment. In accordance with an embodiment, embodiments provide an artificial intelligence/machine learning (AI/ML) engine that monitors and collects both content and consumption analytics associated with content items on a webpage. Based upon an analysis of such metrics, automatic suggestions can be generated for content to be tagged such that the content item can be statically compiled with the website (optimized for viewing speed and user experience), or dynamically fetched/loaded on a load or refresh of the website.

Abstract: Described herein are systems and methods for providing a user interface for dynamic site compilation in a cloud-based content hub environment. In accordance with an embodiment, embodiments provide a user interface that allows a non-technical user, as well as technical users, such as website developers, to “mark”, or flag, various components of a website or page. One category of such marks or flags can indicate that such items marked or flagged with this category of are to be dynamically loaded upon website access (e.g., fetched from a source and then loaded into a website for viewing), while another category of mark or flag can indicate items so marked to be fixed at compile time (e.g., static cache, that is the content is compiled within the published website).

Abstract: Described herein are systems and methods for providing a correlated content organization in a content management system based upon a training set. In accordance with an embodiment, the systems and methods described herein can build a training set based upon observations of received inputs to determine patterns that are used often in content merges. Once a pattern is established, the systems and methods can provide indications of proposed merges based upon the training set and rules established therefrom that fit the same, or similar (e.g., within a defined variant) of the pattern. The system can then receive an indication of whether the suggestion is accepted or rejected, and such decision can be fed back into the learning system.

Abstract: Described herein are systems and methods automatic selection for dynamic site compilation in a cloud-based content hub environment. In accordance with an embodiment, embodiments provide an artificial intelligence/machine learning (AI/ML) engine that monitors and collects both content and consumption analytics associated with content items on a webpage. Based upon an analysis of such metrics, automatic suggestions can be generated for content to be tagged such that the content item can be statically compiled with the website (optimized for viewing speed and user experience), or dynamically fetched/loaded on a load or refresh of the website.

Abstract: Described herein are systems and methods for providing custom component compilation within a cloud-based content hub environment. In accordance with an embodiment, embodiments can allow developers to work with a variety of technologies and optimize a page or site for runtime performance, including in some instances the use of a custom (component) compiler, for use during compilation of a particular component of a website.

Abstract: Described herein are systems and methods for providing a user interface for dynamic site compilation in a cloud-based content hub environment. In accordance with an embodiment, embodiments provide a user interface that allows a non-technical user, as well as technical users, such as website developers, to “mark”, or flag, various components of a website or page. One category of such marks or flags can indicate that such items marked or flagged with this category of are to be dynamically loaded upon website access (e.g., fetched from a source and then loaded into a website for viewing), while another category of mark or flag can indicate items so marked to be fixed at compile time (e.g., static cache, that is the content is compiled within the published website).

Abstract: Described herein are systems and methods automatic selection for dynamic site compilation in a cloud-based content hub environment. In accordance with an embodiment, embodiments provide an artificial intelligence/machine learning (AI/ML) engine that monitors and collects both content and consumption analytics associated with content items on a webpage. Based upon an analysis of such metrics, content can be automatically tagged such that the content item can be statically compiled with the website (optimized for viewing speed and user experience), or dynamically fetched/loaded on a load or refresh of the website.

Abstract: In accordance with an embodiment, described herein is a system and method for providing a content creation tool for use with shoppable content data. A content management system, such as, for example, an Oracle Content and Experience Cloud (OCE) environment, enables the creation of shoppable content that provides a purchasing opportunity directly from the content itself. The system can include, support, or operate in accordance with a content creation tool, that can incorporate aspects of artificial intelligence, for use with shoppable content data, including, for example, performing automatic detection of objects in an image; and automatic discovery of products to be mapped with the shoppable objects or shoppable content; for use in publishing the shoppable content in mobile application, web, or other document formats.