Abstract:
A content validation module receives an electronic media item in a first format. The content validation module may determine whether the electronic media item will contain errors when the electronic media item is converted to a second format. The content validation module may also obtain an error metric for the electronic media item and may refrain from converting the electronic media item to the second format if the error metric exceeds an error threshold.
Abstract:
A Navigation Control File for XML (NCX) generation module receives an electronic media item comprising input text. The electronic media item may also comprise links, where each link comprises a source position and a target position. The NCX generation module generates an NCX file for the electronic media item based on the input text and whether the links within the electronic media item satisfy one or more rules.
Abstract:
In some implementations, legibility of an image may be automatically determined based, at least in part, on text contained in the image. For example, image analysis techniques may be used to identify text components in an image. One or more features of each text component may be determined for use in assessing the legibility of the text component. For example, a classifier trained on the one or more features may provide a confidence level indicative of the legibility of each text component. The confidence level for each of the text components may be compared to a legibility threshold for determining whether the text component is legible or illegible. Based, at least in part, on the determination as to how much of the text in the image is legible or illegible, an overall legibility of the image may be assessed.
Abstract:
A computing device hosting a server identifies one or more potential typographical errors in a work using an initial reference. The computing device sends data indicative of the presence of the potential typographical errors to users. The computing device collects feedback for the work from the users. The feedback for the work indicates whether the potential typographical errors are author-intended strings. The computing device combines the user feedback for the work with user feedback for other works and sorts the combined user feedback based on one or more selected parameters. The computing device determines, based on the sorted user feedback, that one or more of the potential typographical errors includes an acceptable string and updates the initial reference to include the acceptable string.
Abstract:
A method for annotation mapping includes identifying a set of differences between a first version of a document and a second version of the document, the first version comprising annotations. The method further includes generating a position map that maps differences between the first version and the second version, where the position map facilitates the migration of the annotations from the first version to the second version.
Abstract:
Methods and systems for rendering text to simulate human penmanship are described. A text rendering engine converts a text string into an image that can be displayed on a string using one or more seed numbers to influence the rendering and appearance of the text. The text rendering engine may render each character of the text string using a size, weight, slope, or Bezier curve control point selected based on the seed numbers.
Abstract:
A popularity prediction module receives an electronic media item and identifies a feature of the electronic media item. The popularity prediction module applies the feature of the electronic media item to a learned function, where the learned function is determined from a plurality of features from one or more other electronic media items that meet a popularity classification. The popularity prediction module predicts a popularity of the electronic media item based on the comparing, before providing the electronic media item to a user.