Abstract: According to one embodiment, a method, computer system, and computer program product for generating an advertisement is provided. The present invention may include receiving domain corpora; identifying domain-specific terms within each domain comprising the received domain corpora; scoring the identified domain-specific terms based on each of the domains; generating candidate short phrases comprising at least one of the scored domain-specific terms based on the scoring of the scored domain-specific terms; scoring the candidate short phrases; and selecting candidate short phrases based on the scoring of the candidate short phrases.

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: In an approach for user interface widget recommendation, a processor receives a plurality of widgets. A processor applies natural language processing to the plurality of widgets to determine features wherein the features include contexts and layouts associated with the plurality of widgets. A processor trains a widget classifier based on the determined features. The widget classifier predicts a widget type. A processor trains a component classifier based on the widget type associated with the determined features. The component classifier predicts a component type and a component element type.

Abstract: Aspects include real-time context based recipe recommendations including receiving, at a mobile device, an identifier of an available food item that is offered for purchase at a food marketplace. A request for recipes that specifies the identifier of the available food item and a list of identifiers of food items previously selected by the shopper for purchase is sent to a recipe application. At least one recipe selected by the recipe application is received at the mobile device and presented to the shopper. The recipe includes the available food item and at least a subset of the food times previously selected by the shopper. The identifier of the available food item is added to the list of food items previously selected by the shopper for purchase based on determining that the shopper has selected the available food item for purchase.

Abstract: A system for engaging in a recommendation-dialog with a user includes a memory having instructions therein. The system also includes at least one processor in communication with the memory. The at least one processor is configured to execute the instructions to access a recommendation domain, use a structure-mapping technique to generate a data structure based on source material from the recommendation domain, use semantic analyses to generate an ontology based on the data structure and the recommendation domain, generate recommendation-dialog queries based on properties of the data structure, generate a dialog tree based on the ontology and the recommendation-dialog queries, receive a recommendation dialog input, navigate the dialog tree to determine a recommendation, and provide the recommendation to the user.

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: An approach is provided for automatically generating user-specific interaction modes for processing question and answers at the information handling system by receiving a question from a user, extracting user context parameters identifying a usage scenario for the user, identifying first input and output presentation modes for the user based on the extracted user context parameters, monitoring user interaction with the system in relation to the question, and adjusting the first input and output presentation modes based on the extracted user context parameters and detected user interaction with the system.

Abstract: Mechanisms are provided for performing an analysis of content based on a flow of property between entities. The mechanisms analyze a corpus of unstructured documents to identify one or more asset transfer flow relationships between entities. The mechanisms generate an asset transfer flow model defining a flow of an asset between entities based on the one or more asset transfer flow relationships between entities. The mechanisms input the asset transfer flow model into an analysis engine for use in analyzing content. The mechanisms analyze the content using the asset transfer flow model to generate results of the analysis and output the results of the analysis based on the asset transfer flow model.

Abstract: An interleave module interleaves training and task support to assist a user to complete a task while simultaneously providing training to the user. The interleave module helps the user work towards a desired state using a task knowledge base while interjecting appropriate training based on need, the user's mental state and timing constraints. The interleave module may use a variety of input sensors for a subject and the agent to help determine actions to be taken to achieve the task goals and the user's mental state for training.

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: Provided are a computer program product, system, and method for generating a plurality of document plans to generate questions from source text. The declarative source text is processed to generate a plurality of document plan data structures. To generate each document plan data structure, at least a portion of the declarative source text is included in the document plan data structure. A determination is made of at least one relation of arguments in the declarative source text. The determined at least one relation and the arguments are indicated in the document plan data structure. Entity types of the arguments are determined and indicated in the document plan data structure. A natural language generation module processes each of the document plan data structures to generate a plurality of questions, which are stored with the declarative source text.

Abstract: A method, computer system, and a computer program product for generating a custom object is provided. The present invention may include extracting a plurality of constituent components from a static list of previously determined objects associated with a place of purchase. The present invention may then include receiving, from a user, one or more custom objects based on the extracted plurality of constituent components from the place of purchase. The present invention may also include generating, dynamically, a price for each of the one or more selected custom objects based on the extracted plurality of constituent components. The present invention may further include presenting, to the user, the selected one or more custom objects.

Abstract: A computer-implemented method for supporting combinations of intents in a conversation service. In one embodiment, the computer-implemented method provides a conversation service using a set of conversation trees. Each conversation tree within the set of conversation trees comprises a list of intents that define how to answer to a certain type of user input. The computer-implemented method creates an intent graph using the list of intents of each conversation tree within the set of conversation trees. The computer-implemented method adds composite intents to the set of conversation trees using the intent graph to generate a set of updated conversation trees. The computer-implemented method configures the conversation service to use the set of updated conversation trees that comprises composite intents for supporting combinations of intents.

Abstract: Aspects include learning object/action pairs for recipe ingredients. A method includes extracting an ingredient list that includes a plurality of entries from a recipe stored in an electronic format. Each of the plurality of entries includes one or more words. For each multi-word entry in the ingredient list, an ingredient associated with the entry is identified by comparing words contained in the entry to terms in a lexicon of cooking domain terms. It is determined whether an action corresponds to the identified ingredient. The determining includes parsing the entry to locate a verb that is associated with the identified ingredient. Based on determining that an action corresponds to the identified ingredient, a food item action pair that includes the identified ingredient and the located verb is output.

Abstract: A mechanism is provided in a data processing system for rating difficulty of a question. The mechanism receives an input question and generates one or more candidate answers from a corpus of knowledge using a pipeline of software engines. The pipeline of software engines generates a plurality of features extracted from the question, the one or more candidate answers, or the corpus of knowledge. The mechanism then generates a question difficulty score based on the plurality of features using a machine learning model. The machine learning model maps features to assigned weights for scaling the difficulty score.

Abstract: In an approach to determining one or more logical breaks in a digital text, a computer determines a reading speed of a user for a current reading session of a digital text and an available time for the current reading session for the user. The computer then determines, based, at least in part, on the reading speed and the available time, a user range in the digital text for the current reading session, and then one or more possible logical breaks within the user range. The computer further determines a first logical break, based on the determined user range, of the one or more possible logical breaks for the current reading session.

Abstract: Embodiments are directed to a question and answer (QA) pipeline system that adjusts answers to input questions based on a user criteria, thus implementing a content-based determination of access permissions. The QA system allows for information to be retrieved based on permission granted to a user. Documents are ingested and assigned an access level based on a defined information access policy. The QA system is implemented with the defined information access policy, the ingested documents, and the inferred access levels. For the QA system implementation, a user enters a question; primary search and answer extraction stages are performed; candidate answer extraction is performed using only content the user is allowed to access; the candidate answers are scored, ranked, and merged; ranked answers based on user permissions are filtered; and answers are provided to the user.

Abstract: A method, apparatus and program product utilize an automated educational tool to generate or modify one or more multiple choice questions in a question set in connection with tracking a user's attention state to dynamically vary the difficulty of a user assessment performed by the automated educational tool and thereby encourage the user to pay greater attention to the material being presented to the user.

Abstract: Mechanisms for automatically modifying a set of instructions based on an expanded domain specific knowledge base are 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 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.