Microsoft Technology Licensing, LLC

Xiaohui Hou

Jian Wang

Dongmei Zhang

Yingnong Dang

Lei Huang

Yu Zou

Jian-Lai Zhou

Mingqing Xu

Song Huang

Yingjun Qiu

Yue Li

Zhouchen Lin

Jiang Wu

Xianfang Wang

Hongyun Yang

Min Wang

Wenli Zhu

Yongcheng Huang

A method for enabling graphical representation of aggregated data is provided. The method includes accessing aggregated data retrieved from a plurality of on-line sources and receiving selection of a portion of the data through a graphical user interface. The method further includes identifying attributes associated with the portion of the data and generating a graphical representation of the portion of the data.

Graphical representation of aggregated data

Described is a technology that provides an integrated platform for users to use different kinds of digital ink (e.g., handwritten characters, sketched shapes, handwritten formulas) when interacting with computer programs. The platform interprets the user's digital ink input and outputs one or more associated items into an application program. The output items can be customized for different application programs. In one aspect, the platform includes an ink panel having different operating modes for receiving digital ink, and a recognition service that recognizes different types of digital ink. The recognition service may include a unified recognizer that recognizes different types of digital ink, e.g., characters and shapes. Another recognizer may be included such as an equation recognizer. If the recognition result is text while in a non-text mode, the text may be used in a keyword search to locate items; otherwise, the recognition result may be used without keyword searching.

Integrated platform for user input of digital ink

A method for identifying data related to a software security issue is provided. The method includes accessing a software security issue and determining one or more attributes associated with the software security issue. The method also includes accessing aggregated software security data retrieved from a plurality of on-line sources and searching the aggregated software security data for the attributes associated with the security issue. The method further includes associating a portion of the aggregated data with the security issue based on matching the attributes associated with the security issue with contents of the portion of the aggregated data.

Identifying data associated with security issue attributes

A method for identifying a portion of aggregated software security data is described. The method includes accessing aggregated data associated with software vulnerabilities retrieved from a plurality of on-line sources. The method further includes searching a portion of the aggregated data for an exact match to a particular attribute of the data and searching the portion of the aggregated data for one or more partial matches associated with the particular attribute. The method also includes associating the portion of the data with the particular attribute based on the exact match of one or more of the partial matches.

Identifying attributes of aggregated data

A method for enabling access to software security data is provided. The method includes accessing data associated with software vulnerabilities from a plurality of on-line sources. The method further includes aggregating the data from the plurality of on-line sources and identifying attributes associated with the data. The method also includes enabling access to the aggregated data through a graphical user interface that can be used to analyze the data according to the attributes.

Enabling access to aggregated software security information

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.

Digital ink-based search

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.

Unified digital ink recognition

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 subordinate sub-expression analysis component. A method for analyzing a handwritten mathematical expression for a subordinate sub-expression includes identifying sub-expressions based on dominant symbols and determining a character for potential dominant symbols based upon sub-expression information. A determination may be made whether an expression structure candidate is valid and valid expression structure candidates may be stored in a parse tree.

Analyzing subordinate sub-expressions in expression recognition

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).

Software error report analysis

Processes and apparatuses print documents containing embedded interactive code (EIC) information by the use of custom postscript commands that are printer independent, with little overhead when printing, smaller print file size, and faster print times. In order to determine the postscript commands, the EIC array may be represented as a bit for every point, as EIC symbols in which each kind of EIC symbol is a glyph of a font, or as graphics procedures. The postscript approach may be selected based on memory and printing time requirements.

Fast embedded interaction code printing with custom postscript commands

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.

Analyzing scripts and determining characters in expression recognition

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.

Mathematical expression recognition

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.

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Beijing, China

Xiaohui Hou