Abstract: Systems and methods are disclosed herein for generating content based on matching mappings by implementing deconstruction and reconstruction techniques. The system may retrieve a first content structure that includes a first object with a first mapping that includes a first list of attribute values. The system may then search content structures for a matching content structure having a second object with a second list of attributes and a second mapping including second attribute values corresponding to the second list of attributes. Upon finding a match, the system may generate a new content structure having the first object fro m the first content structure with the second mapping from the matching content structure. The system may then generate for output a new content segment based on the newly generated content structure.

Abstract: Systems and methods are disclosed herein for generating content based on format-specific screenplay parsing techniques. The techniques generate and present content by generating new dynamic content structures to generate content segments for output on electronic devices. In one disclosed technique, a first instance of a first character name is identified from the screenplay document. A first set of character data following the first instance of the first character name from the screenplay document and preceding an instance of a second character name from the screenplay document is then identified. Upon identification of the first set of character data, a content structure including an object is generated. The object includes attribute table entries based on the first set of character data. A content segment is generated for output based on the content structure (e.g., a 3D animation of the first character interacting within a scene).

Abstract: Systems and methods are disclosed herein for generating content based on matching mappings by implementing deconstruction and reconstruction techniques. The system may retrieve a first content structure that includes a first object with a first mapping that includes a first list of attribute values. The system may then search content structures for a matching content structure having a second object with a second list of attributes and a second mapping including second attribute values corresponding to the second list of attributes. Upon finding a match, the system may generate a new content structure having the first object from the first content structure with the second mapping from the matching content structure. The system may then generate for output a new content segment based on the newly generated content structure.

Abstract: Systems and methods are disclosed for generating a content structure that can then be used as a content design building block. Specifically, new content can be automatically generated by combining, replacing or mixing and matching objects, actions, settings, effects, audio, etc., from any number of previously stored content structures to create a new content structure, which is then rendered as a new content segment. Content segments are then stitched together to generate a finished content stream. In this way, new and original content can be created without the traditionally expensive and labor-intensive filming or computer animation processes.

Abstract: A method for generating a content depiction of particular content that includes a machine learning system programmed to receive profile data representing preferences for content. The machine learning system identifies preferences for content features based upon the profile data, accesses content data representing the particular content and other content, and classifies features of the content data and content structure data within a content structure database system according to content categories. The machine learning system generates a content structure depiction of the particular content by combining content structure data from the content structure database system, wherein the combining is based upon correlating the identified preferences of the profile with the classified content categories. The machine learning system receives feedback data responsive to the content depiction and reprograms a configuration of the machine learning system for generating a content depiction based upon the feedback data.

Abstract: A method for generating a content depiction of particular content that includes a machine learning system programmed to receive profile data representing preferences for content. The machine learning system identifies preferences for content features based upon the profile data, accesses content data representing the particular content and other content, and classifies features of the content data and content structure data within a content structure database system according to content categories. The machine learning system generates a content structure depiction of the particular content by combining content structure data from the content structure database system, wherein the combining is based upon correlating the identified preferences of the profile with the classified content categories. The machine learning system receives feedback data responsive to the content depiction and reprograms a configuration of the machine learning system for generating a content depiction based upon the feedback data.

Abstract: Systems and methods are disclosed herein for generating supplemental content for media content. One disclosed technique herein generates for display a page of an electronic book. A noun, and a word contextually related to the noun, are identified from the displayed page of the electronic book. Content structures are searched for a content structure that includes a matching object having an object name matching the noun. The content structure includes objects, where each object has attribute table entries. Upon finding an identified attribute table entry of the matching object that matches the related word, a new content structure is generated. The new content structure includes the matching object and the identified attribute table entry. A content segment is generated for output (e.g., for display on the electronic book) based on the new content structure.

Abstract: Systems and methods are disclosed herein for generating content based on matching mappings by implementing deconstruction and reconstruction techniques. The system may retrieve a first content structure that includes a first object with a first mapping that includes a first list of attribute values. The system may then search content structures for a matching content structure having a second object with a second list of attributes and a second mapping including second attribute values corresponding to the second list of attributes. Upon finding a match, the system may generate a new content structure having the first object from the first content structure with the second mapping from the matching content structure. The system may then generate for output a new content segment based on the newly generated content structure.

Abstract: Systems and methods are disclosed herein for generating content based on matching mappings by implementing deconstruction and reconstruction techniques. The system may retrieve a first content structure that includes a first object with a first mapping that includes a first list of attribute values. The system may then search content structures for a matching content structure having a second object with a second list of attributes and a second mapping including second attribute values corresponding to the second list of attributes. Upon finding a match, the system may generate a new content structure having the first object from the first content structure with the second mapping from the matching content structure. The system may then generate for output a new content segment based on the newly generated content structure.

Abstract: Systems and methods are disclosed herein for generating supplemental content for media content. One disclosed technique herein generates for display a page of an electronic book. A noun, and a word contextually related to the noun, are identified from the displayed page of the electronic book. Content structures are searched for a content structure that includes a matching object having an object name matching the noun. The content structure includes objects, where each object has attribute table entries. Upon finding an identified attribute table entry of the matching object that matches the related word, a new content structure is generated. The new content structure includes the matching object and the identified attribute table entry. A content segment is generated for output (e.g., for display on the electronic book) based on the new content structure.

Abstract: A method for generating a content depiction of particular content that includes a machine learning system programmed to receive profile data representing preferences for content. The machine learning system identifies preferences for content features based upon the profile data, accesses content data representing the particular content and other content, and classifies features of the content data and content structure data within a content structure database system according to content categories. The machine learning system generates a content structure depiction of the particular content by combining content structure data from the content structure database system, wherein the combining is based upon correlating the identified preferences of the profile with the classified content categories. The machine learning system receives feedback data responsive to the content depiction and reprograms a configuration of the machine learning system for generating a content depiction based upon the feedback data.

Abstract: Systems and methods are disclosed herein for generating new content segments based on object name identification. A content segment may be received from a device and a content structure is generated based on the content segment. The content structure includes objects each having attributes. The system may search a contact database associated with the device to identify a matching entry of the contact database with a particular object. The comparison matches metadata of the matching entry with an attribute of the particular object. Upon matching, the first object is modified to include a name attribute based on the matching metadata of the matching entry. In response to receiving a request using the name of the particular object to create a new content segment, the system inserts the particular object into a new content structure and a new content segment is generated for display from the new content structure.

Abstract: A method for generating a content depiction of particular content that includes a machine learning system programmed to receive profile data representing preferences for content. The machine learning system identifies preferences for content features based upon the profile data, accesses content data representing the particular content and other content, and classifies features of the content data and content structure data within a content structure database system according to content categories. The machine learning system generates a content structure depiction of the particular content by combining content structure data from the content structure database system, wherein the combining is based upon correlating the identified preferences of the profile with the classified content categories. The machine learning system receives feedback data responsive to the content depiction and reprograms a configuration of the machine learning system for generating a content depiction based upon the feedback data.

Abstract: Systems and methods are disclosed herein for generating supplemental content by generating new content structures from content segments. A content segment that includes a plurality of objects may be received. A content structure based on the content segment may be generated, and a primary object may be identified from the plurality objects. The primary object may include first and second mappings indicating first and second time periods when the primary object appears in the content segment. A new content structure may be generated that includes the primary object, where the first and second mappings may be concatenated. A new content segment may be generated based on the new content structure, and this new content segment may be transmitted to an electronic device.

Abstract: Systems and methods are disclosed herein for generating content based on format-specific screenplay parsing techniques. The techniques generate and present content by generating new dynamic content structures to generate content segments for output on electronic devices. In one disclosed technique, a first instance of a first character name is identified from the screenplay document. A first set of character data following the first instance of the first character name from the screenplay document and preceding an instance of a second character name from the screenplay document is then identified. Upon identification of the first set of character data, a content structure including an object is generated. The object includes attribute table entries based on the first set of character data. A content segment is generated for output based on the content structure (e.g., a 3D animation of the first character interacting within a scene).

Abstract: Systems and methods are disclosed herein for generating new content segments based on object name identification. A content segment may be received from a device and a content structure is generated based on the content segment. The content structure includes objects each having attributes. The system may search a contact database associated with the device to identify a matching entry of the contact database with a particular object. The comparison matches metadata of the matching entry with an attribute of the particular object. Upon matching, the first object is modified to include a name attribute based on the matching metadata of the matching entry. In response to receiving a request using the name of the particular object to create a new content segment, the system inserts the particular object into a new content structure and a new content segment is generated for display from the new content structure.

Abstract: Systems and methods are disclosed for generating content. The system identifies first and second objects in a plurality of frames of a source content segment. The system creates a data structure for each object, where data structures comprise attributes of the respective objects. Furthermore, the data structures are generated such that each object may be reconstructed based on the data of the respective data structure. Later, one of the data structures is modified by changing an attribute. Then, a resulting content segment is generated by a system that reconstructs a first modified object based on the first modified data structure and reconstructs the second object based on the second data structure.

Abstract: Systems and methods are disclosed herein for generating content based on format-specific screenplay parsing techniques. The techniques generate and present content by generating new dynamic content structures to generate content segments for output on electronic devices. In one disclosed technique, a first instance of a first character name is identified from the screenplay document. A first set of character data following the first instance of the first character name from the screenplay document and preceding an instance of a second character name from the screenplay document is then identified. Upon identification of the first set of character data, a content structure including an object is generated. The object includes attribute table entries based on the first set of character data. A content segment is generated for output based on the content structure (e.g., a 3D animation of the first character interacting within a scene).

Abstract: A system accesses content structure that includes a first attribute table including a first list of attributes of a first object, and a first mapping including first attribute values. The first list of attributes of the first object also includes a quality attribute indicating a first quality. After a request to modify quality is received, the system searches a plurality of content structures for a suitable second content structure that comprises a second attribute table including a second list of attributes of a second object. The suitable content structure has another attribute that matches a corresponding attribute of the first list of attributes of the first object and a quality attribute indicating a second quality. The system modifies the first attribute table to include the second list of attributes of the second object. In this way content is generated that is of higher or lower quality than the original content.

Abstract: Systems and methods are disclosed for generating content. The system identifies first and second objects in a plurality of frames of a source content segment. The system creates a data structure for each object, where data structures comprise attributes of the respective objects. Furthermore, the data structures are generated such that each object may be reconstructed based on the data of the respective data structure. Later, one of the data structures is modified by changing an attribute. Then, a resulting content segment is generated by a system that reconstructs a first modified object based on the first modified data structure and reconstructs the second object based on the second data structure.