An example method involves (i) accessing first data representing text, wherein the text defines at least one position representing a particular type of grammatical break between two portions of the text; (ii) identifying, from among the at least one position, a position that is closest to a target position within the text; (iii) based on the identified position within the text, generating second data that represents a proper subset of the text, wherein the proper subset extends from an initial position within the text to the identified position within the text; and (iv) providing output based on the generated second data.

Embodiments are disclosed for automatic enhancement of paragraph justification. A method includes receiving a selection of at least one paragraph, determining a plurality of penalty values for at least one typographic feature by varying a typographic feature value, the penalty values indicating a deviation from an optimal layout of the at least one paragraph, determining at least one optimal penalty value for the at least one typographic feature, the at least one optimal penalty value corresponding to at least one optimal typographic feature value of the at least one typographic feature, determining a priority for each of the at least one typographic feature based on a plurality of justification rules and the at least one optimal penalty value, and updating the at least one typographic feature of the at least one paragraph based on the priority and the at least one optimal typographic feature value.

Embodiments are disclosed for automatic enhancement of paragraph justification. A method includes receiving a selection of at least one paragraph, determining a plurality of penalty values for at least one typographic feature by varying a typographic feature value, the penalty values indicating a deviation from an optimal layout of the at least one paragraph, determining at least one optimal penalty value for the at least one typographic feature, the at least one optimal penalty value corresponding to at least one optimal typographic feature value of the at least one typographic feature, determining a priority for each of the at least one typographic feature based on a plurality of justification rules and the at least one optimal penalty value, and updating the at least one typographic feature of the at least one paragraph based on the priority and the at least one optimal typographic feature value.

The disclosure relates to a user interface presentation method and apparatus, a computer-readable medium and an electronic device. The method comprises: performing, according to the axis of symmetry of a to-be-flipped user interface, mirror image flipping on said user interface, so as to obtain a first interface; determining a first target element in the first interface; performing mirror image flipping on the first target element in the first interface according to the axis of symmetry of the first target element to form a second target element, so as to obtain a second interface; and presenting the second interface. Thus, the flipping of a user interface is realized by means of mirror image flipping, so as to adapt to reading habits of a user.

Embodiments of the present application relate to the technical field of computer information and provide a method and an apparatus for aligning elements in a document, an electronic device and a storage medium. The method includes: obtaining elements contained in a document; assigning the obtained elements into groups; obtaining an inter-group alignment manner between the groups, and obtaining an intra-group alignment manner for elements in each of the groups; and aligning all the groups based on the inter-group alignment manner, and aligning elements in each of the groups based on the intra-group alignment manner. By means of the solution for aligning elements in a document provided by the embodiments of the present application, the efficiency for aligning the elements in the document can be improved.

Systems and methods for automatically determining a content item size may be based on a size of a viewport and a width of a parent element. A script may be configured to determine a size of a viewport, determine a width of a parent element of a resource, and determine a content item size based, at least in part, on the size of the view port and the width of the parent element. A dimension of the determined content item size may be used by a content item selection system to determine a set of content items. A content item selection system may select a content item from the determined set of content items and serve data to effect display of the selected content item in the parent element with the resource.

Systems and methods for automatically determining a content item size may be based on a size of a viewport and a width of a parent element. A script may be configured to determine a size of a viewport, determine a width of a parent element of a resource, and determine a content item size based, at least in part, on the size of the view port and the width of the parent element. A dimension of the determined content item size may be used by a content item selection system to determine a set of content items. A content item selection system may select a content item from the determined set of content items and serve data to effect display of the selected content item in the parent element with the resource.

Systems and methods for automated local story generation and curation are described. In one example embodiment, a server computer receives content from client devices, and processes the content to identify content characteristics. Stories are then generated based on the characteristics of the received content, and the stories are communicated to client devices. In certain embodiments, selection at a client device of an individual piece of content within a story may further be used by the system to provide the client device with a sub-story that includes pieces of content sharing content characteristics with the characteristics of the selected image or video.

Systems and methods for automated local story generation and curation are described. In one example embodiment, a server computer receives content from client devices, and processes the content to identify content characteristics. Stories are then generated based on the characteristics of the received content, and the stories are communicated to client devices. In certain embodiments, selection at a client device of an individual piece of content within a story may further be used by the system to provide the client device with a sub-story that includes pieces of content sharing content characteristics with the characteristics of the selected image or video.

A computer-implemented method for matching user inputted text to stored text. The user inputted text is compared to each of the text strings stored in a database using a Levenshtein distance algorithm. For each comparison, the Levenshtein distance is analyzed to determine exact matches, non-matches, and probable matches. Probable matches are further analyzed using a keyboard distance algorithm to differentiate between matches and non-matches.