A display apparatus includes circuitry to receive an operation of changing a direction of display of a character string displayed in a first direction on a display, and control the display to display a converted character string in a second direction corresponding to the operation of changing. The converted character string is converted from the character string into a target language associated with the second direction.

A personalized preview system to receive a request to access a collection of media items from a user of a user device. Responsive to receiving the request to access the collection of media items, the personalized preview system accesses user profile data associated with the user, wherein the user profile data includes an image. For example, the image may comprise a depiction of a face, wherein the face comprises a set of facial landmarks. Based on the image, the personalized preview system generates one or more media previews based on corresponding media templates and the image, and displays the one or more media previews within a presentation of the collection of media items at a client device of the user.

Similarities between events that include a plurality of dimensions are computed, the similarities computed based on binary comparisons between the events and based on user-specified weights for the dimensions. Multidimensional scaling (MDS) values are calculated based on the computed similarities between the events. A graphical visualization is generated of a temporal plot of the events, the temporal plot comprising a first axis corresponding to time, and a second axis corresponding to the MDS values, and the temporal plot representing overlapping time slices each containing pixels representing a respective subset of the events.

Embodiments of this application are applicable to the field of artificial intelligence technologies, and provide a method and an apparatus for character selection based on character recognition, and a terminal device. The method includes: obtaining a connectionist temporal classification sequence corresponding to text content in an original picture; calculating character coordinates of each character in the connectionist temporal classification sequence; mapping the character coordinates of each character to the original picture, to obtain target coordinates of each character in the original picture; and generating a character selection control in the original picture based on the target coordinates. The character selection control is used to indicate a user to select a character in the original picture. By using the foregoing method, when the user manually selects the character, precision of positioning the character can be improved, and efficiency and accuracy of manually selecting the character can be improved.

Disclosed herein are techniques related to automated generation of regular expressions. In some embodiments, a regular expression generator may receive input data comprising one or more character sequences. The regular expression generator may convert character sequences into a sets of regular expression codes and/or span data structures. The regular expression generator may identify a longest common subsequence shared by the sets of regular expression codes and/or spans, and may generate a regular expression based upon the longest common subsequence.

A method of automated review of communications comprises: receiving, by a computer system, a document from a requestor application; extracting layout information and text from the document; extracting, based on the layout information, values of one or more predefined data items from the text of the document; producing a document validation result by analyzing the one or more data items; embedding, into the document, one or more human-readable comments reflecting the document validation result; and forwarding, to the requestor application, the document comprising the one or more human readable comments.

An information processing apparatus includes a processor configured to acquire specific document data, and in a case where the specific document data includes a text code string, output the text code string included in the specific document data as input data for processing executed by outputting a text code string obtained by text recognition of document data in a predetermined format, in the predetermined format.

An intelligent scoring method and system for a text objective question, the method comprising: acquiring an answer image of a text objective question (101); segmenting the answer image to obtain one or more segmentation results of an answer string to be identified (102); determining whether any of the segmentation results has the same number of characters as the standard answer (103); if no, the answer is determined to be wrong (106); otherwise, calculating identification confidence of the segmentation result having the same number of words as the standard answer, and/or calculating the identification confidence of respective characters in the segmentation result having the same number of words as the standard answer (104); determining whether the answer is correct according to the calculated identification confidence (105). The method can automatically score text objective questions, thus reducing consumption of human resource, and improving scoring efficiency and accuracy.

A method for displaying a video poster based on artificial intelligence is provided. The method includes obtaining a target video and at least one poster according to a user input, calculating a matching degree of an image description text of the at least one poster and a description text keyword of the target video, and sorting the at least one poster according to the matching degree in an order from high to low, to obtain a sorted poster sequence; performing element separation on one of the at least one poster with a highest matching degree in the poster sequence to obtain a main body element and a background element; and processing the main body element, the background element and title information of the target video according to requirements of a target scene to synthesize a new poster.

Disclosed herein are computer-implemented methods; computer-implemented systems; and non-transitory, computer-readable media, for quantifying text similarity. One computer-implemented method includes obtaining a plurality of shortest operation paths including one or more edit pairs for correcting an optical correction recognition (OCR) text string with an edit text string, where each of the one or more edit pairs denotes an operation performable to a character of the OCR text string during correction by the edit text string. A plurality of similarity scores is determined, each corresponding to one of the plurality of shortest operation paths and determined by summing historical similarity scores of the one or more edit pairs of each of the plurality of shortest operation paths. A minimum one of the plurality of similarity scores is selected to quantify text similarity between the OCR text string and the edit text string.