According to certain embodiments, an electronic device may include a display, a memory, and a processor operatively connected to the display and the memory. The processor may be configured to, while receiving user's touch input in a handwriting area of the display, the user's touch input comprising successive input stokes: output the successive input strokes in the handwriting area on the display; determine a first stroke group including some of the successive input strokes, to determine a first character corresponding to the first stroke group, to output the first stroke group in an output area adjacent to the handwriting area on the display, to determine a second stroke group including at least another input stroke received after the some of the successive input strokes, to determine a second character corresponding to the second stroke group, and to output the second stroke group in the output area, move the first stroke group to on one side of the second stroke group on the display.

A generation method implemented by a computer, the generation method including: acquiring, by a processor circuit of the computer, read information generated from a reading result that is a document image obtained by imaging a paper document; and generating, by the processor circuit, an electronic document with a signature image that includes the electronic document and the signature image by adding the signature image obtained by imaging a signature written or stamped on the paper document to an electronic document that corresponds to the acquired read information.

Systems for intelligent sorting of time series data for improved contextual messaging are included herein. An intelligent sorting server may receive time series data comprising a plurality of chat messages. The intelligent sorting server may determine a first order of the plurality of chat messages based on a chronologic order. The intelligent sorting server may use one or more machine learning classifiers to identify candidates for reordering the chat messages. The intelligent sorting server may generate a second order of the chat messages based on the identified candidates for reordering. Accordingly, the intelligent sorting server may present, to a client device, a transcript of the chat messages associated with the second order and an indication that at least one chat message has been repositioned.

In an example, a first set of text may be received from a client device. A set of content items may be selected from among content items based upon the first set of text and a plurality of sets of content item text associated with the content items. A set of terms may be determined based upon the first set of text and the set of content items. A similarity profile associated with the set of terms may be generated. The similarity profile is indicative of similarity scores associated with similarities between terms of the set of terms. Relevance scores associated with the set of terms may be determined based upon the similarity profile. One or more search terms may be selected from among the set of terms based upon the relevance scores. A search may be performed based upon the one or more search terms.

The present disclosure provides a text detection method, a text recognition method and an apparatus, which relate to the field of artificial intelligence technology, in particular to the field of deep learning and computer vision technologies, and can be applied to scenarios such as optical character recognition. The text detection method is: acquiring an image feature of a text strip in a to-be-recognized image; performing visual enhancement processing on the to-be-recognized image to obtain an enhanced feature map of the to-be-recognized image; comparing the image feature of the text strip with the enhanced feature map for similarity to obtain a target bounding box of the text strip on the enhanced feature map.

Methods, systems, and computer-readable storage media for receiving input data including a set of entities of a first type and a set of entities of a second type, providing a set of features based on entities of the first type, the set of features including features expected to be included in entities of the second type, filtering entities of the second type based on the set of features to provide a sub-set of entities of the second type, and generating an output by processing the set of entities of the first type and the sub-set of entities of the second type through a ML model, the output comprising a set of matching pairs, each matching pair in the set of matching pairs comprising an entity of the set of entities of the first type and at least one entity of the sub-set of entities of the second type.

Glyph accessibility techniques are described as implemented by a digital content processing system involving accessing glyphs and glyph alternatives. These techniques include preprocessing techniques in which a base font is used to determine similarity of glyphs within the base font to each other. Glyph metadata that describes this similarity is cached in a storage device and used during runtime to increase efficiency in locating similar glyphs in other fonts.

An information processing apparatus (10) includes a controller (11) that acquires an image containing a figure and a character string and generates association information indicating an association between the figure and the character string based on a positional relationship between the figure and the character string in the image.

The present disclosure provides an information extraction method and apparatus, an electronic device and a readable storage medium, and relates to the field of natural language processing technologies. The information extraction method includes: acquiring a to-be-extracted text; acquiring a sample set, the sample set including a plurality of sample texts and labels of sample characters in the plurality of sample texts; determining a prediction label of each character in the to-be-extracted text according to a semantic feature vector of each character in the to-be-extracted text and a semantic feature vector of each sample character in the sample set; and extracting, according to the prediction label of each character, a character meeting a preset requirement from the to-be-extracted text as an extraction result of the to-be-extracted text. The present disclosure can simplify steps of information extraction, reduce costs of information extraction and improve flexibility and accuracy of information extraction.

A three-dimensional environment analysis method is disclosed. The method includes (i) receiving original point cloud data of a working environment, (ii) processing a map constructed on the basis of the original point cloud data in order to separate out a ground surface, a wall surface and an obstacle in the working environment, (iii) pairing the ground surface with the wall surface according to the degree of proximity between the ground surface and wall surface that are separated out to form one or more adjacent ground-wall pair sets, and (iv) subjecting the one or more adjacent ground-wall pair sets to ray tracing analysis in order to obtain a line-of-sight zone and a non-line-of-sight zone in the working environment. A three-dimensional environment analysis device, a computer storage medium and a wireless sensor system is also disclosed.