Patent application number | Description | Published |
20080205761 | Radical Set Determination For HMM Based East Asian Character Recognition - Exemplary techniques are described for selecting radical sets for use in probabilistic East Asian character recognition algorithms. An exemplary technique includes applying a decomposition rule to each East Asian character of the set to generate a progressive splitting graph where the progressive splitting graph comprises radicals as nodes, formulating an optimization problem to find an optimal set of radicals to represent the set of East Asian characters using maximum likelihood and minimum description length and solving the optimization problem for the optimal set of radicals. Another exemplary technique includes selecting an optimal set of radicals by using a general function that characterizes a radical with respect to other East Asian characters and a complex function that characterizes complexity of a radical. | 08-28-2008 |
20080219556 | Radical-Based HMM Modeling for Handwritten East Asian Characters - Exemplary methods, systems, and computer-readable media for developing, training and/or using models for online handwriting recognition of characters are described. An exemplary method for building a trainable radical-based HMM for use in character recognition includes defining radical nodes, where a radical node represents a structural element of an character, and defining connection nodes, where a connection node represents a spatial relationship between two or more radicals. Such a method may include determining a number of paths in the radical-based HMM using subsequence direction histogram vector (SDHV) clustering and determining a number of states in the radical-based HMM using curvature scale space-based (CSS) corner detection. | 09-11-2008 |
20090003705 | Feature Design for HMM Based Eastern Asian Character Recognition - An exemplary method for online character recognition of East Asian characters includes acquiring time sequential, online ink data for a handwritten East Asian character, conditioning the ink data to produce conditioned ink data where the conditioned ink data includes information as to writing sequence of the handwritten East Asian character and extracting features from the conditioned ink data where the features include a tangent feature, a curvature feature, a local length feature, a connection point feature and an imaginary stroke feature. Such a method may determine neighborhoods for ink data and extract features for each neighborhood. An exemplary Hidden Markov Model based character recognition system may use various exemplary methods for training and character recognition. | 01-01-2009 |
20110229038 | Feature Design for HMM Based Eastern Asian Character Recognition - An exemplary method for online character recognition of East Asian characters includes acquiring time sequential, online ink data for a handwritten East Asian character, conditioning the ink data to produce conditioned ink data where the conditioned ink data includes information as to writing sequence of the handwritten East Asian character and extracting features from the conditioned ink data where the features include a tangent feature, a curvature feature, a local length feature, a connection point feature and an imaginary stroke feature. Such a method may determine neighborhoods for ink data and extract features for each neighborhood. An exemplary Hidden Markov Model based character recognition system may use various exemplary methods for training and character recognition. | 09-22-2011 |
20110246968 | Code-Clone Detection and Analysis - Techniques for detecting, analyzing, and/or reporting code clone are described herein. In one or more implementations, clone-code detection is performed on one or more source code bases to find true and near clones of a subject code snippet that a user (e.g., a software developer) expressly or implicitly selected. In one or more other implementations, code clone is analyzed to estimate the code-improvement-potential (such as bug-potential and code-refactoring-potential) properties of clones. One or more other implementations present the results of code clone analysis with indications (e.g., rankings) of the estimated properties of the respective the clones. | 10-06-2011 |
20110295921 | Hybrid Greatest Common Divisor Calculator for Polynomials - A hybrid greatest common divisor (GCD) calculator analyzes characteristics of polynomials and selects a particular GCD algorithm from multiple available GCD algorithms based on a combination of characteristics of the polynomials. The selected GCD algorithm is then applied to calculate the GCD of the polynomials. | 12-01-2011 |
20120120086 | Interactive and Scalable Treemap as a Visualization Service - Techniques for providing a visualization of an interactive and scalable treemap are described. A service provider hosts large-scale hierarchical data and supports online users who desire to visualize the large-scale hierarchical data in a treemap format on their computing devices. | 05-17-2012 |
20120137182 | Error Report Processing - Techniques for error report processing are described herein. Error reports, received by a developer due to program crashes, may be organized into a plurality of “buckets.” The buckets may be based in part on a name and a version of the application associated with a crash. Additionally, a call stack of the computer on which the crash occurred may be associated with each error report. The error reports may be “re-bucketed” into meta-buckets to provide additional information to programmers working to resolve software errors. The re-bucketing may be based in part on measuring similarity of call stacks of a plurality of error reports. The similarity of two call stacks—a measure of likelihood that two error reports were caused by a same error—may be based in part on functions in common, a distance of those functions from the crash point, and an offset distance between the common functions. | 05-31-2012 |
20120143795 | CROSS-TRACE SCALABLE ISSUE DETECTION AND CLUSTERING - Techniques and systems for cross-trace scalable issue detection and clustering that scale-up trace analysis for issue detection and root-cause clustering using a machine learning based approach are described herein. These techniques enable a scalable performance analysis framework for computing devices addressing issue detection, which is designed as a multiple scale feature for learning based issue detection, and root cause clustering. In various embodiments the techniques employ a cross-trace similarity model, which is defined to hierarchically cluster problems detected in the learning based issue detection via butterflies of trigram stacks. The performance analysis framework is scalable to manage millions of traces, which include high problem complexity. | 06-07-2012 |
20120159434 | CODE CLONE NOTIFICATION AND ARCHITECTURAL CHANGE VISUALIZATION - A code verification system is described herein that provides augmented code review with code clone analysis and visualization to help software developers automatically identify similar instances of the same code and to visualize differences in versions of software code over time. The system uses code clone search technology to identify code clones and to present the user with information about similar code as the developer makes changes. The system may provide automated notification to the developer or to other teams as changes are made to code segments with one or more related clones. The code verification system also helps the developer to understand architectural evolution of a body of software code. The code verification system provides an analysis component for determining architectural differences based on the code clone detection result between the two versions of the software code base. The code verification system also provides a user interface component for displaying identified differences to developers and others involved with the software development process in intuitive and useful ways. | 06-21-2012 |
20120278346 | Frequent Pattern Mining - A system for frequent pattern mining uses two layers of processing: a plurality of computing nodes, and a plurality of processors within each computing node. Within each computing node, the data set against which the frequent pattern mining is to be performed is stored in shared memory, accessible concurrently by each of the processors. The search space is partitioned among the computing nodes, and sub-partitioned among the processors of each computing node. If a processor completes its sub-partition, it requests another sub-partition. The partitioning and sub-partitioning may be performed dynamically, and adjusted in real time. | 11-01-2012 |
20120278658 | Analyzing Software Performance Issues - Execution traces are collected from multiple execution instances that exhibit performance issues such as slow execution. Call stacks are extracted from the execution traces, and the call stacks are mined to identify frequently occurring function call patterns. The call patterns are then clustered, and used to identify groups of execution instances whose performance issues may be caused by common problematic program execution patterns. | 11-01-2012 |
20120278659 | Analyzing Program Execution - A call pattern database is mined to identify frequently occurring call patterns related to program execution instances. An SVM classifier is iteratively trained based at least in part on classifications provided by human analysts; at each iteration, the SVM classifier identifies boundary cases, and requests human analysis of these cases. The trained SVM classifier is then applied to call pattern pairs to produce similarity measures between respective call patterns of each pair, and the call patterns are clustered based on the similarity measures. | 11-01-2012 |
20130173777 | Mining Execution Pattern For System Performance Diagnostics - This application describes a system and method for diagnosing performance problems on a computing device or a network of computing devices. The application describes identifying common execution patterns between a plurality of execution paths being executed by a computing device or by a plurality of computing device over a network. The common execution pattern being based in part on common operations being performed by the execution paths, the commonality being independent of timing of the operations or the sequencing of the operations and individual executions paths can belong to one or more common execution patterns. Using lattice graph theory, relationships between the common execution patterns can be identified and used to diagnose performance problems on the computing device(s). | 07-04-2013 |
20130179911 | CONSUMPTION OF CONTENT WITH REACTIONS OF AN INDIVIDUAL - Techniques for obtaining a reaction of an individual to content and outputting the reaction of the individual with the content are described herein. The techniques may include obtaining the reaction of the individual as the content is displayed to the individual. The reaction may be obtained by capturing a video of the individual. The reaction of the individual and the content may be output at a same time to another individual. These techniques may also include obtaining the reaction of another individual as the content and the reaction of the individual are output to another individual. | 07-11-2013 |
20140049557 | User Interface Tools for Exploring Data Visualizations - Data visualizations may include a large number of data points, some of which may be small, and/or data points that are in close proximity to one another. To assist a user in accurately selecting a desired data point, when displaying a data visualization, a magnification area is simultaneously displayed. The magnification area includes a zoomed-in view of a portion of the data visualization, centered at a current location indicated by a selection device. The magnification area also includes centered vertical and horizontal crosshairs to visually indicate the current location indicated by the selection device. | 02-20-2014 |
20140053091 | Data Exploration User Interface - A data exploration user interface includes a selection area with selectable representations of queryable fields of a data source and a visualization area where query results are displayed as data visualizations. Queries are generated by dragging fields from the selectable area to the visualization area of the user interface. A tree structure of data visualizations may be created by dragging data points out of a displayed visualization and applying additional fields to create a new query and resulting visualization. The tree structure is graphically represented with path indicators that provide historical context for each new data visualization within the visualization are of the user interface. | 02-20-2014 |
20140143688 | ENHANCED NAVIGATION FOR TOUCH-SURFACE DEVICE - An enhanced navigation system detects a predetermined input gesture from a user and presents one or more gesture panels at pre-designated positions on a display of a touch-surface device or positions determined based on where a user is likely to hold the device. The user may navigate content of the application currently presented in the display by providing one or more input gestures within the one or more gesture panels, thus saving the user from moving his/her hands around the display of the touch-surface device while holding the touch-surface device. The enhanced navigation system further enables synchronize one or more gesture definitions with a cloud computing system and/or one or more other devices. | 05-22-2014 |