Methods of facilitating machine learning via a 2-D symbol are disclosed. Features of an object are received in a first computing system having a 2-D symbol creation application module installed thereon. A multi-layer 2-D symbol is formed from the features according to a set of symbol creation rules. 2-D symbol is a matrix of NN pixels partitioned into a number of sub-matrices with each sub-matrix containing one feature, where N is a positive integer. Meaning of the combined features in the 2-D symbol is learned in a second computing system by using an image processing technique to classify the 2-D symbol transmitted from the first computing system. The symbol creation rules determine the importance order, size and location of sub-matrices in the 2-D symbol.

Methods, computer program products, and systems are presented. The methods include, for instance: obtaining a document image with objects and identifying microblocks corresponding to each object. Analyzing a position of a microblock for collinearity with another microblock based on respective positional characteristics and adjustable collinearity parameters. Collinear microblocks are identified into a macroblock and computational data of a key-value pair is created from the macroblock. A heuristic confidence level is associated with the key-value pair. Also based on data cluster formation, a table may be classified and data extracted.

A print data semantic analysis system may comprise a print data handler and a database. The print data handler may include a semantic analyzer and a computer. The semantic analyzer may include a semantic identifier and a semantic operator. Semantic pattern(s), rule(s), and/or semantic category or categories may be stored in mutually associated fashion at the database. The print data handler may be a printer driver having a page description language (PDL) generator. The print data handler may be a raster image processor (RIP), a print server, or a printer having a PDL interpreter. The database may take the form of source code, function(s), lookup or other such table(s), and/or any other suitable format(s). The database may be a function table containing function(s) incorporating the semantic pattern(s), rule(s), and/or semantic category or categories.

A method and system for detecting and extracting accurate and precise structure in documents. A high-resolution image of documents is segmented into a set of tiles. Each tile is processed by a convolutional network and subsequently by a set of recurrent networks for each row and column. A global-lookup process is disclosed that allows future information required for accurate assessment by the recurrent neural networks to be considered. Utilization of high-resolution image allows for precise and accurate feature extraction while segmentation into tiles facilitates the tractable processing of the high-resolution image within reasonable computational resource bounds.

Provided is a method of collecting and managing information relating to medical diagnostic procedures which includes collecting objective information about a plurality of procedures and subjective information about the results of those procedures. The objective information provides information about the parameters of the procedure and the patient who underwent the procedure while the subjective information includes an assessment of the quality of the results of the procedure. This information can be stored in a database. The database can be accessed and the information therein used in connection with understanding the results of past procedures and planning for future procedures.

A method for retrieving an image-text block from a web page is provided, which comprises: retrieving an image node; filtering the image node to obtain candidate image nodes; traversing, for each of the candidate image nodes, a node in sequence toward an ancestor node of the candidate image node in a preset maximum traversal depth until an ancestor node with a text is visited, using the ancestor node with the text as a candidate image-text block; clustering the candidate image-text blocks based on hash values of the path information of the candidate image-text blocks; and determining, for each image-text block cluster, a common ancestor node of the candidate image-text blocks within the image-text block cluster based on the path information of the candidate image-text blocks, and determining path information of the image-text block cluster based on the common ancestor node.

A system and method digital conversion of schedule data includes schedule data stored in a data format corresponding to a scheduling application. A digital imager to captures a digital image of a calendar page sheet into a memory and a processor extracts character data from the digital image. The processor parses temporal data from the character data and determines a calendar entry date from parsed temporal data. The processor further parses event data from the character data and updates an electronic calendar entry for a determined calendar entry date with the event data.

A method and system for detecting and extracting accurate and precise structure in documents. A high-resolution image of documents is segmented into a set of tiles. Each tile is processed by a convolutional network and subsequently by a set of recurrent networks for each row and column. A global-lookup process is disclosed that allows future information required for accurate assessment by the recurrent neural networks to be considered. Utilization of high-resolution image allows for precise and accurate feature extraction while segmentation into tiles facilitates the tractable processing of the high-resolution image within reasonable computational resource bounds.

A computing system/method for enabling a user to improve, via training, a system designed to increase the emotional and/or physical well-being of persons, or designed for other purposes. The system/method includes retrieving a user response from a dialogue database, the user response having already labeled thereto an assigned class having a highest confidence score, the confidence score indicating degree of confidence that context of the retrieved user response is of the assigned class, displaying, the assigned class, along with other classes each having a respective lower confidence score, and receiving an indication of validity of the assigned class. The system/method further includes retrieving of a pair of sequential user response and follow-up prompt from the database, displaying user-selectable ratings, each rating designating a respectively different quality to the follow-up prompt, receiving selection of a rating and a related comment, and associating the selection and the comment to the follow-up prompt.

A computer system apparatus and a method carried out by such apparatus for interacting with a user via a behavior intervention designed to cause an increase in emotional well-being of the user. The behavior intervention has a plurality of conditions to be satisfied. The process includes receiving input data from the user during the behavior intervention, performing, on at least a portion of the received input data having text, semantic analysis to identify terms that satisfy the plurality of conditions and assessing, based on an amount of completeness of satisfying the plurality of conditions, a level of adherence to the behavior intervention. When one or more of the plurality of conditions are determined not as satisfied, the process includes generating a prompt designed to elicit, from the user, a response specific to satisfying the missing conditions.