Abstract: A computer-implemented method according to one embodiment includes identifying an entity within an image that includes one or more missing portions; determining a three-dimensional (3D) model for the entity; and filling in the one or more missing portions of the entity within the image, utilizing the 3D model.

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: A website navigation system has an analysis system which receives a request for an Internet web page from a client device. The analysis system receives web page data associated with the web page from the Internet and performs a data analysis process to organize the web page data for use in a virtual conversation with the user in order to present the web page in an audible format. The analysis system identifies separate elements of the web page from the web page data and extracts information from the separate elements based on the web page data. The analysis system groups the separate elements into categories based on the extracted information and sorts the groups of separate elements based on usage statistics. The analysis system then generates a prompt for being output to the user by the client device as audible output based on the sorted groups of separate elements.

Abstract: Systems, methods, and computer-readable media for constructing a conversation model using documentation of an application programming interface (API) are disclosed. The conversation model can be used to train a natural language classifier. API endpoints may be represented in the API documentation as (verb, resource, element) tuples. These tuples can be converted into intent and parameters of the API endpoints can be converted into entities. In addition, example utterances may be created for each intent. The conversation model can be generated using the intents, example utterances, and/or entities.

Abstract: A computer-implemented method according to one embodiment includes identifying an entity to be filled in within an image, determining a three-dimensional (3D) model for the entity, and filling in the entity within the image, utilizing the 3D model.

Abstract: A chatbot answer database can be generated from a question and answer document. A question/answer processor can receive a document that includes questions and answers. A set of entities can be determined from the answers in the document. A set of triplets can be constructed from the answers, and stored in a chatbot database. For each answer, the question/answer processor can determine text for slots of the triplet based on the entities extracted from the answer. The triplet can be stored as a tree structure in a database of tree structures associated with the document. A chatbot can receive questions, and provide answers based on the database of tree structures associated with the document.

Abstract: A computer-implemented method according to one embodiment includes identifying an entity to be filled in within an image, determining a three-dimensional (3D) model for the entity, and filling in the entity within the image, utilizing the 3D model.

Abstract: A method, computer system, and computer program product for determining a desirability of a product attribute are provided. The embodiment may include extracting a plurality of product features corresponding to one or more products. The embodiment may also include analyzing a plurality of product reviews to determine a sentiment toward the extracted product features. The embodiment may further include calculating a desirability score for each product feature. The embodiment may also include, in response to receiving a user query associated with a product, identifying a product feature to which the received user query relates. The embodiment may further include generating a response to the received user query based on the calculated desirability score.

Abstract: A method, computer program product, and computer system for identifying, by a computing device, that a product of a plurality of products has a likelihood of being wasted. A recipe of a plurality of recipes that includes the product may be identified. One or more attributes of the recipe may be scored. A rating may be assigned to the recipe based upon, at least in part, the one or more attributes of the recipe. The recipe may be returned as a suggestion to use the product before the product is wasted based upon, at least in part, the rating assigned to the recipe.

Abstract: A method, computer program product, and computer system for identifying, by a computing device, that a product of a plurality of products has a likelihood of being wasted. A recipe of a plurality of recipes that includes the product may be identified. One or more attributes of the recipe may be scored. A rating may be assigned to the recipe based upon, at least in part, the one or more attributes of the recipe. The recipe may be returned as a suggestion to use the product before the product is wasted based upon, at least in part, the rating assigned to the recipe.