A computer-implemented method for presenting statistical analysis in a natural language textual output comprising: receiving data to be analyzed by the processor; processing the data according to at least one of a plurality of pre-established statistical analysis types, thereby providing processed data; interpreting the processed data by analyzing the processed data to provide a pre-determined natural language text, thereby providing interpreted data; and generating a natural language textual output for the interpreted data according to at least one pre-established rule for converting the interpreted data to a natural language textual output.

Methods and systems for automated language detection for domain names are disclosed. In some embodiments, a method for detecting a language of an Internationalized Domain Name (IDN) comprises receiving, by an I/O interface, a string of characters for the IDN; receiving training data, including a plurality of multi-gram analyses for a set of languages; analyzing, by a processor, the string of characters based on the training data, wherein the analyzing includes extracting a set of multi-grams from the string of characters and comparing the extracted set of multi-grams with the training data; detecting the language of the IDN based on results of the analyzing. In some embodiments, the method further comprises comparing the detected language of the IDN with a user selected language and using the IDN to generate a domain name, if the comparing indicates that the detected language of the IDN is consistent with the user selected language.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for content evaluation. In one aspect, a method includes identifying a first document object model for a resource, the first document object model being associated with a performance profile, the performance profile specifying performance factors for content item presentation positions of the resource. A first similarity measure can be computed for first document object model based on the first document object model and a second document object model for the resource, the second document object model for the resource being a previous document object model for the resource. A new performance profile can be computed for the resource if the first similarity measure does not meet a similarity threshold.

A method of creating an electronic file corresponding to a printed artifact may include receiving an image file of a document page. The method may include analyzing the image file to detect a potential form identifier on the document page and automatically (without human intervention) performing a search to identify an actual form that corresponds to the potential form identifier. The method may further include validating that the image file is of a document page that corresponds to the actual form, locating a probable fill-in field on the document page and mapping the probable fill-in field to an actual fill-in field of the actual form.

Systems and processes are disclosed for predicting words in a text entry environment. Candidate words and probabilities associated therewith can be determined by combining a word n-gram language model and a unigram language model. Using the word n-gram language model, based on previously entered words, candidate words can be identified and a probability can be calculated for each candidate word. Using the unigram language model, based on a character entered for a new word, candidate words beginning with the character can be identified along with a probability for each candidate word. In some examples, a geometry score can be included in the unigram probability related to typing geometry on a virtual keyboard. The probabilities of the n-gram language model and unigram model can be combined, and the candidate word or words having the highest probability can be displayed for a user.

A system and method for adapting a speech recognition and generation system. The system and method include providing a speech recognition and generation engine that processes speech received from a user and providing a dictionary adaptation module that adds out of vocabulary words to a baseline dictionary of the speech recognition and generation system. Words are added by extracting words that are encountered and adding out of vocabulary words to the baseline dictionary of the speech recognition and generation system.

Systems and methods for converting a natural language sentence into a computer-readable primitive sentence and extracting information therefrom are disclosed. A method includes identifying, by a processing device, a verbal block in the natural language sentence, splitting, by the processing device, the natural language sentence into one or more logical clauses, determining, by the processing device, a type for each logical clause, where the type indicates whether each logical clause contains an ambiguous verbal block, disambiguating, by the processing device, the ambiguous verbal block within each logical clause, where each verbal block is considered independently of a noun phrase, and constructing, by the processing device, the computer-readable primitive sentence for each ambiguous verbal block by duplicating a shared noun phrase of the ambiguous verbal block. The computer-readable primitive sentence improves functioning of a computing device by allowing the computing device to process the natural language sentence to obtain information therefrom.

Computer system, methods, mobile app, and media to guarantee the quality of a language translation of content using a computer network of translators and reviewers communicating in real-time. The accuracy, and hence quality, of the translation is ensured by incorporating “real-time” quality checks comprising randomly inserted errors into an original human translation and evaluating if a reviewer detects the errors. By using a plurality of reviewers for grading each translation, while detecting and eliminating reviewers that are not competent, the quality of a translation is guaranteed. The level of quality is also controlled by increasing (higher quality) and decreasing (lower quality) the type and amount of errors to be detected by the reviewers. Therefore, a computerized system is able to guarantee the quality of a translation into any language and without knowing that language, or the translators who translate it, or the reviewers who grade the translators.

A method of adjusting the probability of a presentation being randomly selected during random play based on user feedback where the length of delay prior to the user pressing the skip button causes a modification in the probability of that presentation being displayed again.

A similarity between character strings is assessed by identifying first and second character strings as candidate similar character strings, determining a frequency of occurrence for at least one of the first and second character strings from a collection of character strings, and designating the first and second character strings as similar based on the determined frequency of occurrence.