Nielsen Consumer LLC

Javier Martínez Cebrián

Roberto Arroyo

David Jiménez

David Jiménez-Cabello

Jose Javier Yebes Torres

David Montero

Methods, apparatus, systems, and articles of manufacture are disclosed that determine related content. An example apparatus includes processor circuitry to generate a segment-level graph by sampling segment-level edges among segment nodes representing text segments, the segment-level graph including segment node embeddings representing features of the segment nodes; cluster the text segments to form entities by applying a first GAN based model to the segment-level graph to update the segment node embeddings; generate a multi-level graph by (a) generating an entity-level graph including hypernodes representing the entities and sampled entity edges connecting ones of the hypernodes, and (b) connecting the segment nodes to respective ones of the hypernodes using relation edges; generate hypernode embeddings by propagating the updated segment node embeddings using a relation graph; and cluster the entities by product by applying a second GAN based model to the multi-level graph, the multi-level graph to generate updated hypernode embeddings.

Methods, systems, articles of manufacture, and apparatus to determine related content in a document

Methods, apparatus, systems, and articles of manufacture are disclosed to categorize image text. An example apparatus includes region detection model training circuitry to identify candidate regions in an input image that include text, and generate bounding boxes around respective ones of the identified candidate regions. The example apparatus also includes mask application circuitry to improve optical character recognition (OCR) by applying a mask to the input image, wherein the mask removes content of the input image except for portions of the input image within the bounding boxes, and OCR circuitry to perform OCR on the masked input image to obtain text data within the bounding boxes.

Methods, systems, articles of manufacture and apparatus to categorize image text

Methods, apparatus, systems, and articles of manufacture are disclosed for processing an image using visual and textual information. An example apparatus includes at least one memory, instructions in the apparatus, and processor circuitry to execute the instructions to detect regions of interest corresponding to a product promotion of an input digital leaflet, extract textual features from the product promotion by applying an optical character recognition (OCR) algorithm to the product promotion and associating output text data with corresponding ones of the regions of interest, determine a search attribute corresponding to the product promotion, generate a first dataset of candidate products corresponding to the product in the product promotion by comparing the search attribute against a second dataset of products, and select a product from the first dataset of candidate products to associate with the product promotion, the product selected based on a match determination.

Methods, systems, articles of manufacture, and apparatus for processing an image using visual and textual information

Example methods, apparatus, and articles of manufacture to classify labels based on images using artificial intelligence are disclosed. An example apparatus includes a regional proposal network to determine a first bounding box for a first region of interest in a first input image of a product; and determine a second bounding box for a second region of interest in a second input image of the product; a neural network to: generate a first classification for a first label in the first input image using the first bounding box; and generate a second classification for a second label in the second input image using the second bounding box; a comparator to determine that the first input image and the second input image correspond to a same product; and a report generator to link the first classification and the second classification to the product.

Growing community of inventors

Madrid, Spain

Javier Martínez Cebrián