Patent classifications
G06V30/148
METHOD AND APPARATUS FOR GENERATING PREDICTION INFORMATION, AND ELECTRONIC DEVICE AND MEDIUM
Disclosed are a method and apparatus for generating prediction information, and an electronic device and a medium. One embodiment of the method comprises: acquiring at least one input word; generating a word vector of each input word of the at least one input word to obtain a word vector set, wherein the at least one input word is obtained by performing word segmentation on target input text; generating an input text vector on the basis of the word vector set; and on the basis of the input text vector and a user vector, generating prediction information for predicting a user intention, wherein the user vector is obtained on the basis of user historical record information. In this embodiment, prediction information for predicting a user intention is generated, such that the popping up of unnecessary information is reduced. A user can be prevented from being disturbed, thereby improving the user experience.
SETTING TERMINAL, SETTING METHOD AND PROGRAM
Provided is a setting management system that makes setting operation of a device efficient. A setting terminal includes a storage unit that stores a scenario of a setting process related to a device to be set, an input unit that is USB connected to the device to be set and inputs information to the device to be set, a progress determination unit that determines a progress of a scenario of a setting process based on timing of an input by the input unit and the scenario stored in the storage unit, and a setting operation unit that inputs, to the device to be set, setting information via the input unit according to the progress of the scenario determined by the progress determination unit.
SEMANTIC MATCHING BETWEEN A SOURCE SCREEN OR SOURCE DATA AND A TARGET SCREEN USING SEMANTIC ARTIFICIAL INTELLIGENCE
Semantic matching between a source screen or source data and a target screen using semantic artificial intelligence (AI) for robotic process automation (RPA) workflows is disclosed. The source data or source screen and the target screen are selected on a matching interface, semantic matching is performed between the source data/screen and the target screen using an artificial intelligence/machine learning (AI/ML) model, and matching graphical elements and unmatched graphical elements are highlighted, allowing the developer to see which graphical elements match and which do not. The matching interface may also provide a confidence score of the individual matches, provide an overall mapping score, and allow the developer to hide/unhide the matched/unmatched graphical elements. Activities of an RPA workflow may be automatically created based on the semantic mapping that can be executed to perform the automation.
Implicit Coordinates and Local Neighborhood
A system and method are disclosed for using a local neighborhood for determining similar targets in different documents or using implicit coordinates for obtaining a coordinate location of a target. The local neighborhood method may include identifying a first target in a first document; identifying one or more first elements within a first distance range from the first target; creating a first local neighborhood based on the identifying; determining that that first local neighborhood is similar to a third local neighborhood in a second document; and determining a second target in the second document that corresponds to the first target in the first document, based on the determining the similarity. The implicit coordinates method may include performing OCR on the first document to find the first target; and obtaining a first location of the first target by using at least one of OCR or element recognition.
DIVIDING DEVICE
A dividing device includes: an acquisition unit that acquires a plurality of words constituting a character string one by one from a head of the character string; a first calculation unit that calculates a forward division likelihood indicating a likelihood of dividing the character string at a position in front of a first word acquired by the acquisition unit and a backward division likelihood indicating a likelihood of dividing the character string at a position immediately after the first word; a detection unit that detects a division point based on the forward division likelihood and the backward division likelihood, the division point being a position at which the character string is divided; a generation unit that generates a chunk by dividing the character string at the division point; and an output unit that outputs the chunk.
Cloud-Based Multi-Camera Quality Assurance Architecture
Data is received that is derived from each of a plurality of inspection camera modules forming part of a quality assurance inspection system. The data includes a feed of images of a plurality of objects passing in front of the respective inspection camera module. Thereafter, the received data is separately analyzed by each inspection camera module using at least one image analysis inspection tool. The results of the analyzing can be correlated for each inspection camera module on an object-by-object basis. The correlating can use timestamps for the images and/or detected unique identifiers within the images and can be performed by a cloud-based server and/or a local edge computer. Access to the correlated results can be provided to a consuming application or process.
Image Enhancement in a Genealogy System
Methods, systems, and computer-program products for image enhancement include receiving an image and optionally a user request, classify the image, crop image components of the image, restore cropped image components of the image, colorized restored image components, and reconstruct the image from the colorized, restored image components and other components. The other components may include text components that are restored in a separate treatment pipeline.
Word recognition method, apparatus and storage medium
The present invention provides a word recognition method. The method includes: acquiring an image of a word to be recognized; recognizing edges of each character of the word to be recognized from the image of the word to be recognized; determining a geometric position of the word to be recognized; stretching the geometric position of the word to be recognized to a horizontal position; and recognizing the word to be recognized in the horizontal position.
Method and apparatus for improved presentation of information
A method and apparatus comprising generating a dynamic personalized webpage is disclosed. At least two webpages are loaded in a fashion that is hidden from the user. Content from the at least two webpages is extracted based on classification “of interest” by an artificial intelligence algorithm. A dynamic personalized webpage comprising extracted content is then generated and displayed to the user. In the preferred embodiment, the user's dynamic personalized webpage will be filled with advertisements tailored to the user and the user would receive at least some revenue from advertisements.
SYSTEMS AND TECHNIQUES TO MONITOR TEXT DATA QUALITY
Disclosed are a system, apparatus and techniques for evaluating a dataset to confirm that the data in the dataset satisfies a data quality metric. A machine learning engine or the like may evaluate text strings within the dataset may be of arbitrary length and encoded according to an encoding standard. Data vectors of a preset length may be generated from the evaluated text strings using various techniques. Each data vector may be representative of the content of the text string and a category may be assigned to the respective data vector. The category assigned to each data vectors may be evaluated with respect to other data vectors in the dataset to determine compliance with a quality metric. In the case that a number of data vectors fail to meet a predetermined quality metric, an alert may be generated to mitigate any system errors that may result from unsatisfactory data quality.