Abstract: A plurality of personalized news feeds are generated from input feeds including digital content items based on a dynamic taxonomy data structure. Entities are extracted from the input feeds and relationship strengths are obtained for the extracted entities and the digital content items. The dynamic taxonomy data structure is updated with the extracted entities and entries for the digital content news items are included at the corresponding branches based on the relationship strengths. Attributes are obtained for the entities and those entities corresponding to the trending topics are identified. Personalized news feeds are generated including the digital content items listed under the entities. Digital content items are added or removed from the digital content feeds based on one or more entity attributes.

Abstract: A device may identify standard parameters and real-time parameters associated with content of a content type, and may process the content type, the standard parameters, and the real-time parameters, with a parameter unification model, to generate derived parameters for the content. The device may process the derived parameters and the content type, with a multi-level linear regression machine learning model, to calculate a content score for the content, and may process the derived parameters and the content score, with a linear regression machine learning model, to calculate a quantity of f-NFTs to generate for the content and a divestment ratio. The device may create a unique reference to the content, and may create an NFT for the content based on the unique reference. The device may generate the quantity of f-NFTs for the content based on the NFT, and may provide the quantity of f-NFTs to a content exchange.

Abstract: A machine learning (ML) based code transformation system that transforms a source programming code developed using a source library for execution on a source platform into remediated code for execution on a target platform is disclosed. Metadata extracted from the source programming code is used to detect the source programming language, source libraries, and the source platform. The metadata also enables modularizing the source programming code based on the functionality and identifying a node from a plurality of nodes in a communication network to execute the various source code modules. A similarity map is generated mapping the source libraries to the target libraries and the source code modules that are incompatible with the target platform are identified and remediated with similar target code modules using the similarity map.

Abstract: A plurality of personalized news feeds are generated from input feeds including digital content items based on a dynamic taxonomy data structure. Entities are extracted from the input feeds and relationship strengths are obtained for the extracted entities and the digital content items. The dynamic taxonomy data structure is updated with the extracted entities and entries for the digital content news items are included at the corresponding branches based on the relationship strengths. Attributes are obtained for the entities and those entities corresponding to the trending topics are identified. Personalized news feeds are generated including the digital content items listed under the entities. Digital content items are added or removed from the digital content feeds based on one or more entity attributes.

Abstract: A device may receive developer profile data identifying developers associated with different technology communities and technology domains and may assign attributes and weights to the developer profile data to generate weighted developer profile data. The device may utilize a first machine learning model, with the weighted developer profile data, to calculate similarity indexes identifying developers associated with multiple technology communities, and may process the weighted developer profile data and the similarity indexes, with a second machine learning model, to calculate developer activity scores for the technology domains and for developer classifications. The device may identify, based on the developer activity scores, a particular developer profile with a greatest developer activity score, and may process the particular developer profile, with a third machine learning model, to determine an engagement strategy for addressing the particular developer.

Abstract: A dynamic application testing and scoring system that tests applications under various tenets and categorizes the applications to be published, to be further reviewed or rejected. The results from administering a plurality of tests to an application are analyzed by applying rulesets that pertain to criteria under each of the tenets. An application score is determined from the analysis using weights associated with the tenets, priority levels of the criteria and the severity levels of the rulesets. The application score identifies a position for the application on a scoring scale relative to two trust threshold values. The application is categorized based on the position. Feedback regarding the categorization is received and the trust threshold values on the scoring scale can be adjusted if the categorization in the feedback is different from the categorization produced by the scoring system.

Abstract: A device may receive video data associated with a video, and may identify image data associated with the video data and that corresponds to a frame of the video. The device may process the image data, with an image analysis model, to determine an image compliance score associated with a policy and with context of the image data, and may identify text data associated with the video data. The device may process the text data, with a text analysis model, to determine a text compliance score associated with the policy and with context of the text data, and may determine, based on the image compliance score and the text compliance score, an aggregate compliance score associated with the frame. The device may determine whether the aggregate compliance score satisfies a threshold associated with the policy, and may perform actions based on whether the aggregate compliance score satisfies the threshold.

Abstract: An Artificial Intelligence (AI) based payments processing system analyzes data from a user's purchase invoice to identify a combination of payment modes to be used to pay for the user's purchases thereby maximizing the savings to the user while accounting for the user preferences. A savings oriented model including a mix and match model and a dynamic decision tree scoring model generates a savings based best offer suggesting the payment modes to be used by analyzing the user's purchases based on the offers associated with the purchased products. A user behavior model generates a user behavior based best offer by further accounting for user preferences. Based on the user's autopay settings, the payments processing system may automatically initiate payment for the user's purchases or may display the best offers to the user before initiating the payments.

Abstract: A dynamic application testing and scoring system that tests applications under various tenets and categorizes the applications to be published, to be further reviewed or rejected. The results from administering a plurality of tests to an application are analyzed by applying rulesets that pertain to criteria under each of the tenets. An application score is determined from the analysis using weights associated with the tenets, priority levels of the criteria and the severity levels of the rulesets. The application score identifies a position for the application on a scoring scale relative to two trust threshold values. The application is categorized based on the position. Feedback regarding the categorization is received and the trust threshold values on the scoring scale can be adjusted if the categorization in the feedback is different from the categorization produced by the scoring system.

Abstract: An intelligent return path data (iRPD) system enables transmission of return path data via a communication network for a television connected to a non-hybrid set top box (STB). The iRPD system is configured to receive the key codes of the keys pressed on a remote control device along with the date time stamps and the location information. The iRPD system analyzes the keypress data along with the date time stamps to recognize the channels accessed in programming operations and the non-programming control operations executed by a viewer operating the remote control device. The viewer's behavior pattern is thus recorded and analyzed to identify the viewer. Upon identifying the viewer, various functions such as collecting the viewership statistics, implementing metered usage billing or ecommerce activities are enabled.

Abstract: A device may receive video data associated with a video, and may identify image data associated with the video data and that corresponds to a frame of the video. The device may process the image data, with an image analysis model, to determine an image compliance score associated with a policy and with context of the image data, and may identify text data associated with the video data. The device may process the text data, with a text analysis model, to determine a text compliance score associated with the policy and with context of the text data, and may determine, based on the image compliance score and the text compliance score, an aggregate compliance score associated with the frame. The device may determine whether the aggregate compliance score satisfies a threshold associated with the policy, and may perform actions based on whether the aggregate compliance score satisfies the threshold.

Abstract: A multimedia content distribution system can receive and store multimedia content items from content providers. The system may also receive and store content distribution information from a variety of different data sources that is related to the multimedia content items and the distribution of the multimedia content items. The system may predict viewership for a multimedia content item for future release dates based on the content distribution information, and provide automated control of the distribution of the multimedia content item, which may include distribution over a content distribution network.

Abstract: An intelligent return path data (iRPD) system enables transmission of return path data via a communication network for a television connected to a non-hybrid set top box (STB). The iRPD system is configured to receive the key codes of the keys pressed on a remote control device along with the date time stamps and the location information. The iRPD system analyzes the keypress data along with the date time stamps to recognize the channels accessed in programming operations and the non-programming control operations executed by a viewer operating the remote control device. The viewer's behavior pattern is thus recorded and analyzed to identify the viewer. Upon identifying the viewer, various functions such as collecting the viewership statistics, implementing metered usage billing or ecommerce activities are enabled.

Abstract: Methods and systems including computer programs encoded on a computer storage medium, for receiving a request for digital content to be provided from a plurality of items of digital content, determining a set of content scores for each item of digital content in the plurality of items of digital content, each content score in the set of content scores being specific to a user of the plurality of users, and a respective item of digital content, calculating a combined score deviation for each item of digital content based on a difference between a minimum content score and a maximum content score of the set of content scores of a respective item of digital content, determining at least one candidate item of digital content, the at least one candidate item of digital content having a lowest combined score deviation among combined score deviations of the plurality of items of digital content, and providing the at least one candidate item of digital content.

Abstract: An intelligent VR (IVR) system receives a VR content item and automatically augments the VR content item with additional or ancillary content. The intelligent VR system initially identifies within the VR content item, valid textual and non-textual objects that have ancillary content associated therewith. The IVR system provides hotspots that signify presence of the ancillary content for the valid objects during a display of the VR content item. The hotspots and the ancillary content are positioned for display corresponding to pixel blocks including the valid objects. The ancillary content is selected for the hotspots based on a spatial and temporal extent of display of the valid objects. The hotspots with respective ancillary content items and the VR content item are streamed to a head mounted display (HMD) for display to a viewer.

Abstract: Methods and systems including computer programs encoded on a computer storage medium, for interactive content recommendation. In one aspect, a method includes receiving a request for content by a user, determining a user intent based on the received request, providing to the user a first attribute responsive to the user intent, receiving a first attribute value responsive to the first attribute, providing a second attribute, and receiving a second attribute value responsive to the second attribute. A particular content vector including a first content attribute and a second content attribute for a particular content item is identified where the first content attribute and the second content attribute sufficiently match the first attribute value and the second attribute value. The particular content item is provided as a suggested content item, and, responsive to a user selection of the particular content item, provided for presentation on the user device.

Abstract: A system may receive, from multiple data providers or multiple platforms, data associated with content, a content provider that provides the content, and multiple channels via which the content is provided or consumed. The data may include first data, received from a first data provider or a first platform, that is associated with a different file type than second data received from a second data provider or a second platform. The system may include a data model associated with the first data and the second data. The system may aggregate the data from the multiple data providers or the multiple platforms. The system may identify a relationship between the first data and the second data. The first data and the second data may be different types of data. The system may perform an action based on the relationship between the first data and the second data.

Abstract: Methods and systems including computer programs encoded on a computer storage medium, for receiving a request for digital content to be provided from a plurality of items of digital content, determining a set of content scores for each item of digital content in the plurality of items of digital content, each content score in the set of content scores being specific to a user of the plurality of users, and a respective item of digital content, calculating a combined score deviation for each item of digital content based on a difference between a minimum content score and a maximum content score of the set of content scores of a respective item of digital content, determining at least one candidate item of digital content, the at least one candidate item of digital content having a lowest combined score deviation among combined score deviations of the plurality of items of digital content, and providing the at least one candidate item of digital content.

Abstract: Methods and systems including computer programs encoded on a computer storage medium, for interactive content recommendation. In one aspect, a method includes receiving a request for content by a user, determining a user intent based on the received request, providing to the user a first attribute responsive to the user intent, receiving a first attribute value responsive to the first attribute, providing a second attribute, and receiving a second attribute value responsive to the second attribute. A particular content vector including a first content attribute and a second content attribute for a particular content item is identified where the first content attribute and the second content attribute sufficiently match the first attribute value and the second attribute value. The particular content item is provided as a suggested content item, and, responsive to a user selection of the particular content item, provided for presentation on the user device.

Abstract: An intelligent VR (IVR) system receives a VR content item and automatically augments the VR content item with additional or ancillary content. The intelligent VR system initially identifies within the VR content item, valid textual and non-textual objects that have ancillary content associated therewith. The IVR system provides hotspots that signify presence of the ancillary content for the valid objects during a display of the VR content item. The hotspots and the ancillary content are positioned for display corresponding to pixel blocks including the valid objects. The ancillary content is selected for the hotspots based on a spatial and temporal extent of display of the valid objects. The hotspots with respective ancillary content items and the VR content item are streamed to a head mounted display (HMD) for display to a viewer.