Abstract: The disclosed embodiments include a system, computer program product, and computer-implemented method configured to modify a knowledge graph. The disclosed embodiments seek to improve the process of expanding a knowledge graph by identifying information that is useful and relevant to the needs of the users based on questions being asked by users. In one embodiment, the information is collected using a gaming platform. The disclosed embodiments augment the knowledge graph, by adding new entities and/or relationships, based on the gathered information.

Abstract: A computer-implemented method includes receiving input questions through interactive digital content and determining demographic designators associated the questions. The method further includes grouping together similar input questions and, for each group of similar questions, creating an answer. Scripts are created from each answer and each script and the corresponding group of similar input questions is recorded into a data repository.

Abstract: A computer program product for computer generation of digital content, said computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processing resource to cause the processing resource to determine demographic designators associated with users of user devices that render interactive digital contents; group together similar input questions input into the interactive digital contents of the user devices; for each group of similar questions, create an answer to each group of similar questions; create a script from each answer; record each script and the corresponding group of similar input questions in a data repository; and insert a script from the data repository into a digital content template.

Abstract: A method includes determining an environmental condition and determining that demand for a target data object is below a threshold value under the environmental condition. The method further includes identifying an offering whose demand is above the threshold value under the environmental condition and that includes the target data object. Also, the method includes generating digital content containing the offering and information about the target data object and transmitting the digital content to a user device over a network.

Abstract: Mechanisms are provided for automatically identifying required tools for performing actions specified in electronic documents. The mechanisms perform natural language processing of content of a training corpus of electronic documents to identify associations of action terms with required tools for performing actions corresponding to the action terms. The mechanisms train an ontology model based on the identified associations. The mechanisms perform analysis of electronic documents of one or more other corpora based on the trained ontology model to identify required tools for performing actions specified in the electronic documents. The mechanisms annotate one or more of the electronic documents of the one or more corpora to include required tools annotation metadata identifying tools required to perform actions corresponding to action terms present in the one or more electronic documents.

Abstract: Mechanisms for training a human user to perform an operation and provided. The mechanisms generate a domain specific knowledge base comprising a set of entities and corresponding domain specific attributes and expand the domain specific knowledge base to include values for the domain specific attributes through an automated bootstrap learning process that performs natural language processing and analysis of natural language content using a set of pre-condition annotated action terms, thereby generating an expanded domain specific knowledge base. The mechanisms evaluate an input from another device identifying an action associated with an entity in the set of entities, based on a retrieved domain specific attribute value and the retrieved pre-condition annotation from the expanded domain specific knowledge base. The mechanisms output a notification to a user computing device indicating whether the input is correct or incorrect to thereby train a user associated with the user computing device.

Abstract: Mechanisms for automatically modifying a set of instructions based on an expanded domain specific knowledge base is provided. The mechanisms generate a domain specific knowledge base comprising a set of entities and corresponding domain specific attributes and expand the domain specific knowledge base to include values for the domain specific attributes through an automated bootstrap learning process that performs natural language processing and analysis of natural language content using a set of pre-condition annotated action terms. The mechanisms receive electronic content comprising an initial set of instructions to perform an operation and evaluate the initial set of instructions based on the expanded domain specific knowledge base to identify a missing instruction. The mechanisms modify the initial set of instructions to include an additional instruction based on the missing instruction and thereby generate a modified set of instructions.

Abstract: Mechanisms for bootstrapping knowledge acquisition from a limited knowledge domain are presented. Natural language content is received and a primary and secondary portion of natural language content are identified within the natural language content. The secondary portion of natural language content is analyzed to identify indications of meaning directed to elements of the primary portion of natural language content. Features related to the secondary portion of the natural language content indicate meaning directed to the primary portion of the natural language content. A collection of domain knowledge is generated from an analysis of the primary and secondary portions of the natural language content and stored to provide meaningful responses to requests.

Abstract: A method for distributing a plurality of funds to a plurality of content creators is provided. The method may include registering a content creator using a plurality of content creator identifying information when a user visits a content creator webpage. The method may also include receiving a plurality of user interaction data when the user visits the content creator webpage of a registered content creator. The method may further include generating an invoice based on the received plurality of user interaction data. The method may also include disbursing at least one payment to the registered content creator based on the generated invoice.

Abstract: A method for distributing a plurality of funds to a plurality of content creators is provided. The method may include registering a content creator using a plurality of content creator identifying information when a user visits a content creator webpage. The method may also include receiving a plurality of user interaction data when the user visits the content creator webpage of a registered content creator. The method may further include generating an invoice based on the received plurality of user interaction data. The method may also include disbursing at least one payment to the registered content creator based on the generated invoice.

Abstract: An approach is provided that captures a digital image of an object, such as a piece of home improvement hardware, that has any number of facets. From the captured digital image, the approach determines an actual size the object's facets, and further identifies any number of hardware tools that can be used to manipulate the hardware object based in part on the actual size of the object's facets.

Abstract: An approach is provided that captures a digital image of an object that has a number of facets. The approach further determines the actual sizes of various facets found on the object. The actual sizes of the facets are used to identify compatible objects based, with the compatible objects being objects that can work with the object.

Abstract: A method, system and computer-usable medium are disclosed for recommending instructional content according to a user's level of skill. User input requesting instructional content is parsed to generate features associated with skills referenced in the request. The resulting features and user input are then processed to identify individual instances of instructional content that contain at least one skill referenced in the user input. In turn, the identified individual instances of instructional content are presented in ranked order to the user as recommended instructional content.

Abstract: A method, system and computer-usable medium are disclosed for assessing requisite skills to recommend instructional content to a user. A corpus of instructional content and a corpus of user skills content associated with a user are parsed to generate features associated with individual skills respectively referenced within the two corpora. The resulting features are then used to cross-reference individual instances of instructional content that contain at least one skill associated with the user. The individual instances of instructional content containing at least one skill associated with the user are then provided in ranked order as recommended instructional content to the user.

Abstract: Mechanisms for identifying hidden meaning in a portion of natural language content are provided. A primary portion of natural language content is received and a secondary portion of natural language content is identified that references the natural language content. The secondary portion of natural language content is analyzed to identify indications of meaning directed to elements of the primary portion of natural language content. A probabilistic model is generated based on the secondary portion of natural language content modeling a probability of hidden meaning in the primary portion of natural language content. A hidden meaning statement data structure is generated for the primary portion of natural language content based on the probabilistic model.

Abstract: Mechanisms for identifying hidden meaning in a portion of natural language content are provided. A primary portion of natural language content is received and a secondary portion of natural language content is identified that references the natural language content. The secondary portion of natural language content is analyzed to identify indications of meaning directed to elements of the primary portion of natural language content. A probabilistic model is generated based on the secondary portion of natural language content modeling a probability of hidden meaning in the primary portion of natural language content. A hidden meaning statement data structure is generated for the primary portion of natural language content based on the probabilistic model.

Abstract: Mechanisms for identifying hidden meaning in a portion of natural language content are provided. A primary portion of natural language content is received and a secondary portion of natural language content is identified that references the natural language content. The secondary portion of natural language content is analyzed to identify indications of meaning directed to elements of the primary portion of natural language content. A probabilistic model is generated based on the secondary portion of natural language content modeling a probability of hidden meaning in the primary portion of natural language content. A hidden meaning statement data structure is generated for the primary portion of natural language content based on the probabilistic model.