Abstract:
Systems, methods, and machine readable media are provided for classifying customer feedback. In exemplary embodiments, text is captured from at least one source relating to at least one product. The text is scanned and a score is produced for sentiment for the at least one product. The text is filtered into parts of speech and key words to produce filtered text. The filtered text is transformed into a term-document matrix. A risk score is calculated and prioritized based on the term-document matrix and the sentiment score. The product and the associated risk score are reported to a subject matter expert (SME), where a determination is made whether the product is reportable or non-reportable.
Abstract:
The present invention relates to the context of the personal identification procedures, validation of identity documents, etc. In particular, the present invention proposes to offer a process and a semi-automatic and secure apparatus for recognition and validation of personal identities, identity documents or both at once.
Abstract:
Methods, apparatuses and electronic devices for generating a feature vector, as well as searching methods, apparatuses and electronic devices are disclosed. The method for generating a feature vector includes: acquiring data information; extracting a semantic feature from the data information, to acquire semantic feature information; and acquiring a feature vector of the data information by using a preset function, with the semantic feature information as a parameter. The technical solution identifies picture information by recognizing semantics of image information and matching the semantics of the image information with natural language descriptions. Different from conventional image search schemes of existing search engines, this technical solution does not need to retrieve a text description of image information, but retrieves and identifies images based on the content of the image information. Therefore, results with higher accuracy may be returned compared with the existing text-based image search.
Abstract:
A computerized method for generating and displaying structured topics of a taxonomy in different formats is provided. The computerized method includes generating a categorized topic viewer graphical user interface allowing a user to select a textual model defining a corpus of documents to explore by delimiting a healthcare treatment product; generating in the categorized topic viewer graphical user interface, in response to an input of the user delimiting the healthcare treatment product, at least one of a plurality of tools; generating in a topic mapping graphical user interface an interactive map illustrating the number of documents for a first class for each corresponding country; generating in a trend generating graphical user interface at least one of a plurality of tools; and modifying each of the categorized topic viewer graphical user interface, the topic mapping graphical user interface and the trend generating graphical user interface in response to at least one input of the user into at least one taxonomy filter such that data displayed by each of the categorized topic viewer graphical user interface, the topic mapping graphical user interface and the trend generating graphical user interface display data related to a second class of the corpus of documents, the second class being a subcategory of the first class.
Abstract:
Systems and methods of determining image captions are provided. In particular, metadata and image recognition data associated with an image can be obtained. The metadata and image recognition data can be used to generate one or more image tags associated with the image. One or more caption templates associated with the image can further be determined. Upon a selection of one or more of the image tags, an image caption can be generated using a caption template based at least in part on the user selection. The generated caption can be a sentence or phrase providing semantic and/or contextual information associated with the image.
Abstract:
An example system includes a feature engine to determine a plurality of features of a document in a segment of an image. The system also includes a probability engine to determine a probability that the document is a particular document type based on the plurality of determined features. The system also includes a classify engine to classify the segment as the particular document type or a generic document type based on at least one of the determined probabilities.
Abstract:
A method of detecting Moire artefacts in a digital image comprises calculating at least one parameter relating to at least one feature of the digital image. The at least one parameter is compared to at least one corresponding threshold, wherein the at least one threshold is determined by a machine learning process, based on a set of example images and reference parameters for the set of example images. It is determined whether the digital image contains Moire artefacts based on the results of the comparing.
Abstract:
A method of processing image data of an electronic device is provided. The method includes dividing the image data into at least one segment corresponding to a feature of at least part of the image data, determining a category corresponding to the at least one segment, and displaying the at least one segment in a converted form based on the category.
Abstract:
Examples disclosed herein relate to selection of machine-readable link type. Examples include acquisition of an electronic document, selection of a machine-readable link type for evaluation, and a decision of whether at least one characteristic of the document satisfies at least one evaluation metric for use of the selected type of machine-readable link.