A handwritten data capture method creates handwritten data including a plurality of pieces of stroke data that is based on writing performed on each page of a paper medium having a plurality of pages. The handwritten data capture method includes: acquiring the plurality of pieces of stroke data created based on the writing sequenced in a writing order; displaying the pieces of stroke data together on a display device; accepting an input of a break position of the pieces of stroke data; identifying a continuous portion of the pieces of stroke data based on the break position and the writing order; updating the display device to display the identified continuous portion of the pieces of stroke data in the writing order; and repeating the accepting, the identifying, and the updating until a given operation is received.

The present disclosure discloses a word vector retrofitting method. The method includes obtaining, by a computing device, a first model and a second model that are generated when original word vectors are trained, the first model being configured to predict a context according to an inputted word, and the second model being configured to predict a target word according to a context; inputting a corpus unit from a target corpus into the first model, inputting an output of the first model into the second model, and determining losses generated by the first model and the second model when the second model outputs the corpus unit; and retrofitting the first model and the second model according to the losses.

Provided is a method for preventing an accident related to children or pets that may occur by a home appliance using artificial intelligence. According to the present disclosure, the method for preventing the accident comprises comparing a distance between the home appliance and a generation position of the voice signal and a reference distance when the generation position of the voice signal is outside of the home appliance. Then, the present disclosure enables switching a door of the home appliance to a lock state when a distance between the home appliance and the generation position of the voice signal is less than the reference distance. Thus, the present disclosure may enable controlling the home appliance to prevent children or pets from entering an inside of the home appliance.

Provided is a method for preventing an accident related to children or pets that may occur by a home appliance using artificial intelligence. According to the present disclosure, the method for preventing the accident comprises comparing a distance between the home appliance and a generation position of the voice signal and a reference distance when the generation position of the voice signal is outside of the home appliance. Then, the present disclosure enables switching a door of the home appliance to a lock state when a distance between the home appliance and the generation position of the voice signal is less than the reference distance. Thus, the present disclosure may enable controlling the home appliance to prevent children or pets from entering an inside of the home appliance.

An embodiment of the present invention generates natural language content from a set of keywords in accordance with a template. Keyword vectors representing a context for the keywords are generated. The keywords are associated with language tags, while the template includes a series of language tags indicating an arrangement for the generated natural language content. Template vectors are generated from the series of language tags of the template and represent a context for the template. Contributions from the contexts for the keywords and the template are determined based on a comparison of the series of language tags of the template with the associated language tags of the keywords. One or more words for each language tag of the template are generated to produce the natural language content based on combined contributions from the contexts for the keywords and the template.

Tailoring textual content to a target audience by receiving an input of a user, wherein the input of the user includes textual data, identifying a target audience of the textual data based at least in part on the input of the user, determining a style of the target audience, wherein the style is a variety of language used by the target audience, generating a modification recommendation to the textual data of the input of the user based at least in part on the textual data and the determined style.

Examples of a sentence phrasing system are provided. The system may obtain a user question from a user. The system may obtain question entailment data from a plurality of data sources. The system may implement an artificial intelligence component to identify a word index from the question entailment data and to identify a question premise from the user question. The system may implement a first cognitive learning operation to determine an answer premise corresponding to the question premise comprising a second-word data set. The system may determine a subject component corresponding to the question premise. The system may generate an object component and a predicate component from the second-word data set corresponding to the subject component. The system may generate an integrated answer relevant for resolving the user question and comprising the subject component, the object component, and the predicate component concatenated to form an answer sentence.

Systems and methods for displaying hierarchical table headers as disclosed. The systems and methods can include operations performed by a viewer engine. The operations can include detecting a user interaction with a display of a portion of data. The operations can further include determining a second portion of the data to display. The operations can additionally include obtaining data information for the second portion of the data. The data information can include information about headers for the second portion of the data and information about child-parent relationships between the headers. The operations can include determining one or more hierarchical headers for the second portion of the data. The operations can further include rendering a table including the second portion of the data. The operations can additionally include displaying a display depicted the one or more hierarchical headers and a subset of the table including the second portion of the data.

Data security using randomized features, provides improved protection of user data, within a cloud infrastructure. Files received are broken apart into data blocks then randomly written into storage locations that are recorded in sequence into a key comprising an array of pointers. Data blocks may be randomly sized between maximum and minimum parameters. Storage locations may first be tested to prevent unwanted overwrites of preexisting data, undersized locations may receive a partial write, plus a pointer to an overflow location into which the remainder of data is written. Randomized data storage is separate and isolated from pointers based key storage via separate communication channels, and separate storage infrastructures. Download speeds may be boosted via parallel processing of data blocks out of storage and into reassembly according to the pointers key sequence. Re-assembled files may be worked upon then saved back into the cloud infrastructure.

A system for hyper-dimensional computing for inference tasks may be provided. The device comprises an item memory for storing hyper-dimensional item vectors, a query transformation unit connected to the item memory, the query transformation unit being adapted for forming a hyper-dimensional query vector from a query input and hyper-dimensional base vectors stored in the item memory, and an associative memory adapted for storing a plurality of hyper-dimensional profile vectors and for determining a distance between the hyper-dimensional query vector and the plurality of hyper-dimensional profile vectors, wherein the item memory and the associative memory are adapted for in-memory computing using memristive devices.