Abstract: 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.

Abstract: Described herein is technology for, among other things, accessing error report information. It involves various techniques and tools for analyzing and interrelating failure data contained in error reports and thereby facilitating developers to more easily and quickly solve programming bugs. Numerous parameters may also be specified for selecting and searching error reports. Several reliability metrics are provided to better track software reliability situations. The reliability metrics facilitate the tracking of the overall situation of failures that happen in the real word by providing metrics based on error reports (e.g., failure occurrence trends, failure distributions across different languages).

Abstract: A forward pass through a sequence of strokes representing a handwritten equation is performed from the first stroke to the last stroke in the sequence. At each stroke, a path score is determined for a plurality of symbol-relation pairs that each represents a symbol and its spatial relation to a predecessor symbol. A symbol graph having nodes and links is constructed by backtracking through the strokes from the last stroke to the first stroke and assigning scores to the links based on the path scores for the symbol-relation pairs. The symbol graph is used to recognize a mathematical expression based in part on the scores for the links and the mathematical expression is stored.

Abstract: Described is a technology, such as implemented in a computational software program, by which a minimal polynomial is efficiently determined for a radical expression over the ring Z of integer numbers or the ring Q of rational numbers. The levels of the radical are grouped into a level permutation group that is used to find a level permutation set. An annihilation polynomial is found based upon the level permutation set. The annihilation polynomial is factored, and a selection mechanism selects the minimal polynomial based upon the annihilation polynomial's factors.

Abstract: 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.

Abstract: This disclosure describes a user interface and techniques for an interactive graphical representation of large scale data on a display. The disclosure describes how large scale data may be viewed using multiple linked charts. In one implementation, a user interface comprises an overview chart. The user may use chart controller(s) to designate one or more portions of the overview chart viewable in subsequent charts. The user may navigate between the overview chart and the subsequent charts using the chart controller(s).

Abstract: A method for researching and developing a recognition model in a computing environment, including gathering one or more data samples from one or more users in the computing environment into a training data set used for creating the recognition model, receiving one or more training parameters defining a feature extraction algorithm configured to analyze one or more features of the training data set, a classifier algorithm configured to associate the features to a template set, a selection of a subset of the training data set, a type of the data samples, or combinations thereof, creating the recognition model based on the training parameters, and evaluating the recognition model.

Abstract: A method for performing symbolic computations on a mathematical expression. The mathematical expression may be converted to a tree structure having one or more parent nodes and one or more child nodes. Each parent node may be a mathematical operation. Each child node may be a mathematical expression on which the mathematical operation is performed in a specified order. Each child node may be in a hierarchical relationship to one of the parent nodes. The parent nodes, the child nodes or both may be manipulated to perform a first symbolic computation on the mathematical expression.

Abstract: An opinion system infers the opinion of a sentence of a product review based on a probability that the sentence contains certain sequences of parts of speech that are commonly used to express an opinion as indicated by the training data and the probabilities of the training data. When provided with the sentence, the opinion system identifies possible sequences of parts of speech of the sentence that are commonly used to express an opinion and the probability that the sequence is the correct sequence for the sentence. For each sequence, the opinion system then retrieves a probability derived from the training data that the sequence contains an opinion word that expresses an opinion. The opinion system then retrieves a probability from the training data that the opinion words of the sentence are used to express an opinion. The opinion system then combines the probabilities to generate an overall probability that the sentence with that sequence expresses an opinion.

Abstract: Techniques for providing arbitrary precision floating number (APFN) processing are disclosed. In some aspects, an APFN store may be used to store a large number (i.e., an APFN) having many significant digits, which in turn may enable a high degree of precision in mathematical operations. An APFN module may be used to create and define the APFN store. The APFN module may enable a user to define a precision (significant digits) for the large number that corresponds to the size of an array of bytes in the APFN store that are allocated for storing the large number. In further aspects, the APFN store may be used to store additional intermediary data and a resultant.

Abstract: Described is a multi-path handwriting recognition framework based upon stroke segmentation, symbol recognition, two-dimensional structure analysis and semantic structure analysis. Electronic pen input corresponding to handwritten input (e.g., a chemical expression) is recognized and output via a data structure, which may include multiple recognition candidates. A recognition framework performs stroke segmentation and symbol recognition on the input, and analyzes the structure of the input to output the data structure corresponding to recognition results. For chemical expressions, the structural analysis may perform a conditional sub-expression analysis for inorganic expressions, or organic bond detection, connection relationship analysis, organic atom determination and/or conditional sub-expression analysis for organic expressions. The structural analysis also performs subscript, superscript analysis and character determination. Further analysis may be performed, e.g.

Abstract: A method for converting a polynomial expression to a data structure for symbolic computation. One or more variables in the polynomial expression may be determined. The variables may be stored in a first array. One or more terms in the polynomial expression may be determined. One or more exponents of the variables in each term may be determined. The exponents may be stored in a second array. One or more coefficients of the terms may be determined. The coefficients may be stored in a third array.

Abstract: A method and system for controlling a transmission window size, wherein a transmission condition of the transmission path between a transmitting element and a receiving element is checked when at least one of the transmitting and receiving elements moves from a first access network to a second access network. Then, the transmission window size is changed in response to the result of said checking step. Thereby, the transmission window can be decreased actively to thereby accelerate the control procedure and improve resource utilization.

Abstract: A mechanism for recognizing and inputting handwritten mathematical expressions into a computer by providing a part of a multi-path framework is described. The part of the multi-path framework includes a symbol grouping and recognition component that is designed to group input strokes that correspond to a handwritten mathematical expression into a symbol and to recognize the symbol based upon information associated with the grouped input strokes. A method for grouping and recognizing symbols of a handwritten mathematical expression includes receiving a plurality of input strokes corresponding to a handwritten mathematical expression, grouping the plurality of input strokes into symbols, recognizing the symbols based upon information, such as shape and time series information, associated with the grouped input strokes. Intra-group and inter-group information associated with the plurality of input strokes may be utilized to group the input strokes.

Abstract: A mechanism for recognizing and inputting handwritten mathematical expressions into a computer by providing part of a multi-path framework is described. The part of the multi-path framework includes a subscript/superscript analysis and character determination component that is designed to identify subscript and superscript elements. A method for analyzing a handwritten mathematical expression includes receiving a symbols corresponding to handwritten mathematical expression input strokes, identifying subscript and/or superscript structures, and determining a character for each symbol of the set. A graph of vertexes and edges may be created based upon the set of symbols and the graph may be searched to determine optimized candidates.

Abstract: A mechanism for recognizing and inputting handwritten mathematical expressions into a computer by providing a multi-path framework is described. The framework may include symbol grouping and recognition, tabular structure analysis, subordinate sub-expression analysis, subscript/superscript analysis and character determination, and semantic structure analysis components. A method for recognizing a handwritten mathematical expression includes receiving a plurality of input strokes corresponding to a handwritten mathematical expression and providing a candidate list of recognized candidate expressions based upon the input strokes. Input strokes are grouped into symbols, tabular structures are determined, dominant symbol candidates and subordinate symbols are determined, and subscript and superscript structures are determined.

Abstract: The present invention generally relates to methods and devices as well as handheld stations and computer program products for sending video game content to handheld mobile terminals, comprising broadcasting common video game content to handheld mobile communication terminals via a digital video broadcast handheld channel, to enable said handheld mobile terminals to execute video game applications.

Abstract: Systems and methods for adjusting a source image aspect ratio to match a different target display aspect ratio are described. In one aspect, the systems and methods determine that a source image has a first aspect ratio that is different than a second aspect ratio of a target display. Responsive to this determination, primary visual content of the source image is automatically detected. Dimensions and position of a crop of the source image are automatically calculated such that the crop preserves at least a subset of the primary visual content in the crop. Additionally, the crop is based on the second aspect ratio.

Abstract: Described is a unified digital ink recognizer that recognizes various different types of digital ink data, such as handwritten character data and custom data, e.g., sketched shapes, handwritten gestures, and/or drawn pictures, without further participation by a user such as recognition mode selection or parameter input. For a custom item, the output may be a Unicode value from a private use area of Unicode. Building the unified digital ink recognizer may include defining the data set to be recognized, extracting features of training samples corresponding to the dataset items to build a recognizer model, evaluating the recognizer model using testing data, and modifying the recognizer model using tuning data. The extracted features may be processed into feature data for a multi-dimensional nearest neighbor recognizer approach; the extracted features for the samples of each class is calculated and combined into the feature set for this class in the resulting recognizer model.

Abstract: Described is searching directly based on digital ink input to provide a result set of one or more items. Digital ink input (e.g., a handwritten character, sketched shape, gesture, drawing picture) is provided to a search engine and interpreted thereby, with a search result (or results) returned. Different kinds of digital ink can be used as search input without changing modes. The search engine includes a unified digital ink recognizer that recognizes digital ink as a character or another type of digital ink. When the recognition result is a character, the character may be used in a keyword search to find one or more corresponding non-character items, e.g., from a data store. When the recognition result is a non-character item, the non-character item is provided as the result, without keyword searching. The search result may appear as one or more item representations, such as in a user interface result panel.