Abstract: A computer system receives a definition of a group that includes an indication of a hierarchal rank of group members, a plurality of content items that correspond to the group, and identifying information indicating at least one group member that corresponds to a content item. A search input by a first user is detected and an indication of a hierarchal rank for the first user is stored. Determining a weight to assign to a search result includes comparing a hierarchal rank of at least one group member that corresponds to the first content item with the hierarchal rank of the first user.

Abstract: While receiving a user input of content of a first document, a computer system, dynamically and in real time, identifies relevant information items from a plurality of information feeds. Specifically, one or more other documents is obtained in a collection of documents that are relevant to the first document being entered by a user. When it is determined that changes in member documents of the set of one or other documents satisfies a stabilization criterion while receiving the user input, related terms are extracted from the content of the first document and the one or more other documents and used to identify the relevant information items including the related terms from the plurality of information feeds that is distinct from the collection of documents. The relevant information items are then presented on a display for the user.

Abstract: Selecting data from a source text corpus for training a semantic data analysis system includes selecting an item of the text corpus, validating the item, extracting at least one section of the item, determining a length of each of the at least one section of the item, and subdividing each of the sections having a length greater than a predetermined amount into a plurality of fragments that are deemed to be similar. The predetermined amount may be approximately twice a size of a fragment. A fragment may have approximately 100 words or between 40 and 60 words. Fragments from different items may be deemed to be dissimilar. Sections having a length less than the predetermined amount may be ignored. Validating the item may include parsing editorial notes and other accompanying data. The source text corpus may be Wikipedia. The item may be an article.

Abstract: Searching for documents includes retrieving objects from a physical media image using a camera from a smartphone, a user selecting a subset of the objects, forming a search query based on the subset of objects, and applying the search query to a search engine to search for the documents. Retrieving objects from a media image may include waiting for a view of the camera to stabilize. Waiting for the view of the camera to stabilize may include detecting changing content of a video flow provided to the camera and/or using motion sensors of the camera to detect movement. Retrieving objects may include the smartphone identifying possible subsets of objects in the media image. The user selecting a subset of the objects may include the smartphone presenting at least some of the possible subsets to the user and the user selecting one of the possible subsets.

Abstract: This application is directed to vectoring a raster image in which an electronic device detects a contour of a component in the raster image, builds tangent vectors for each point of the contour and identifies a plurality of segmentation points on the contour. One or more points of sharp angle are identified on the contour in accordance with a determination that each point of sharp angle corresponds to two distinct tangent vectors and that an angle between the two distinct tangent vectors falls below a predefined threshold. A respective one of the segmentation points is positioned at each identified point of shape angle. The electronic device approximates a piecewise smooth fitting curve (e.g., a piecewise Bezier curve) having two or more fitting segments to connect the plurality of segmentation points on the contour. The piecewise smooth fitting curve is thereby provided to vectorize the raster image.

Abstract: Recording audio information from a meeting includes determining which audio input audio device (smartphones) correspond to which meeting participant, measuring volume levels in response to each of the meeting participants speaking, identifying one of the participants is speaking based on stored voice profiles and/or relative volume levels at each of the smartphones, recording on a first channel audio input at a first smartphone corresponding to the speaker, identifying another one of the participants is speaking based on stored voice profiles and/or relative volume levels at each of the smartphones, recording on a second channel, separate from the first channel, audio input at a second smartphone corresponding to the other speaker, and merging the first and second channels to provide a storyboard that includes audio input from the channels and identification of speakers based on which specific ones of the channels contains the audio input.

Abstract: This application is directed to recognizing unstructured information based on hints provided by structured information. A computer system obtains unstructured information collected from a handwritten or audio source, and identifies one or more terms from the unstructured information. The one or more terms includes a first term that is ambiguous. The computer system performs a recognition operation on the first term to derive a first plurality of candidate terms for the first term, and obtains first contextual information from an information template associated with the unstructured information. In accordance with the first contextual information, the computer system selects a first answer term from the first plurality of candidate terms, such that the first term is recognized as the first answer term.

Abstract: Protecting a fragment of a document includes automatically detecting the fragment without user intervention based on the content of the fragment and/or the context of the fragment within a set of documents, selectively encrypting the fragment to prevent unauthorized access, and providing an alternative view of the fragment that prevents viewing and access of content corresponding to the fragment unless a decryption password is provided. Automatically detecting the fragment may include detecting numbers and alphanumeric sequences of sufficient length that do not represent commonly known abbreviations, detecting generic terms, detecting proper names, detecting terms signifying a type of content, detecting mutual location of terms and sensitive content, and/or detecting user defined terms. The generic terms may correspond to password, passcode, credentials, user name, account, ID, login, confidential, and/or sensitive. The proper names may be names of financial organizations and security organizations.

Abstract: Enhancing image quality of an initial full image of a document page includes obtaining the initial full image of a document page, determining that at least a subset of text in the initial full image does not meet a predefined readability criterion, identifying at least one of a plurality of page fragments in the initial full image of the document page for enhancement, and sending an instruction to a mobile device to provide a photograph of the at least one of the page fragments. The photograph provides a separate fragment image for the at least one of the page fragments. The separate fragment image is then obtained from the mobile device and merged into the initial full image to provide an enhanced full image.

Abstract: Providing a view of relevant items of a content collection includes identifying a current context based temporal parameters, spatial parameters, navigational parameters, lexical parameters, organizational parameters, and/or events, evaluating each of the items of the content collection according to the current context to provide a value for each of the items, and displaying a subset of the items corresponding to highest determined values. The temporal parameters may include a time of recent access of an item, frequency of access of an item, frequency of location related access of an item, and frequency of event related access of an item. Temporal patterns of accessing items may be numerically assessed based on time of day, time of week, and/or time of month. Evaluating each item may include determining a distance from a separating hyperplane using a support vector machine classification method.

Abstract: Integrating an application and a chat session includes a first user identifying content from the application, wherein the application is independent of any chat session, the first user initiating the chat session with at least a second user that is remote from the first user by transmitting the content from the first user to the second user, where the first and second user establish the chat session in response to the content being transmitted, and the first user and the second user sharing the content in connection with the chat session. The content may be a portion of a photograph, a portion of an image, a portion of text from a document, and/or a portion of a screen. The portion may be automatically identified following the user pointing and marking up the content. The first user may mark up the content before transmitting it to the second user.

Abstract: A digital content clipping system receives an indication that a first web page has been accessed by a first user, and searches a repository of digital content clips associated with the first web page. In accordance with a determination that the repository does not include any user-generated digital content clips associated with the first web page, the system offers one or more first clipping options based on predefined clip templates, receives selection, by the first user, of one of the first clipping options, extracts a digital content clip of the first web page in accordance with the selected one of the first clipping options, and stores the digital content clip of the first web page in a first clip collection associated with the first web page.

Abstract: Determining if a document is a text page includes partitioning the document into a plurality of cells, scaling each of the cells to a standardized number of pixels to provide a corresponding snippet for each of the cells, using a classifier to examine the snippets to determine which of the cells are classified as text and which of the cells are not classified as text, determining a volume of text for the document based on a total amount of text in the document corresponding to a sum of an amount of text in each of the cells classified as text, and determining that the document is a text page in response to the total amount exceeding a pre-determined threshold. In response to the total amount being less than the pre-determined threshold, cells not classified as text may be examined further. The classifier may be provided by training a neural net.

Abstract: Protecting a fragment of a document includes automatically detecting the fragment without user intervention based on the content of the fragment and/or the context of the fragment within a set of documents, selectively encrypting the fragment to prevent unauthorized access, and providing an alternative view of the fragment that prevents viewing and access of content corresponding to the fragment unless a decryption password is provided. Automatically detecting the fragment may include detecting numbers and alphanumeric sequences of sufficient length that do not represent commonly known abbreviations, detecting generic terms, detecting proper names, detecting terms signifying a type of content, detecting mutual location of terms and sensitive content, and/or detecting user defined terms. The generic terms may correspond to password, passcode, credentials, user name, account, ID, login, confidential, and/or sensitive. The proper names may be names of financial organizations and security organizations.

Abstract: Modifying a document being entered by a user by adding data from at least one of a plurality of news items relevant to the document includes determining other documents in a collection of documents that are relevant to the document being entered by the user, constructing a filter based on content of the document being entered by the user and on the other documents, presenting on a display the plurality of news items selected from a plurality of news feeds according to the filter, the user selecting from the display at least one of the news items, and the user inserting data from the at least one of the news items into the document. The document may be a note and the collection of documents may be a notebook. The note and the notebook may be provided by the OneNote product from Microsoft Corporation and/or by the Evernote product.

Abstract: Managing information for a project includes identifying content items corresponding to the project, identifying project participants that access the content items, sharing at least some of the content items with at least some of the project participants, prioritizing the project participants based, at least in part, on contribution by the project participants to the content items, and displaying, on a wearable device of a master user, the project participants according to priority levels thereof. The wearable device may be a smart watch. The project participants may be displayed in a plurality of groups of the project participants according to prioritizing levels. The prioritizing levels may take into account development milestones, production milestones, contract closures, external demos, customer meetings, and/or project phase completion schedules. The master user may use a gesture to remove at least one of the groups and to expand remaining groups displayed on the wearable device.

Abstract: Facilitating replying to received email messages includes presenting a selectable set of fast reply tokens that correspond to snippets of multimedia content, providing a mechanism to superimpose a selected subset of the fast reply tokens on to different portions of the received email message to compose an annotated email messages, wherein the fast reply tokens are separate from any reply email text, and sending the annotated email message. The fast reply tokens may include action icons, status icons, emoticons, emojis, expressive elements, clip art, highlighters, geometric shapes, arrows, short tunes, audio clips, video clips, abbreviated standard texts, and freehand notes. Facilitating replying to received email messages may also include providing cultural adaptations and localization of fast reply tokens based on a setting provided by a recipient of the annotated email message.

Abstract: Vectorizing a raster image includes identifying a connectivity component in the raster image, detecting a contour of the connectivity component, building tangent vectors for each point of the contour, for each sharp angle of the contour, positioning a segmentation point of two segments at a point thereof, for each location of high curvature of the contour, positioning segments proximal thereto, composing an optimization task to approximate a piecewize Bezier curve, solving the optimization task to provide a vectorization of the raster image, and, in response to there not being a sufficient number of segments, adding additional segments. Vectorizing a raster image may also include applying perspective, color, brightness and contrast correction to the raster image and building a binary black-white representation of the raster image prior to identifying the connectivity component. The optimization task may minimize a root-mean square deviation of the piecewize Bezier curve.

Abstract: Providing incremental search suggestions as a user enters terms in a search query includes determining if a recently entered term is in a context-free dictionary of natural language phrases, generating natural language query search completion candidates corresponding to terms provided by the user in the search query if the recently entered term is in the context free dictionary, determining if the recently entered term contains a keyword hint if the recently entered term is not in the context free dictionary, generating keyword search completion candidates if the recently entered term is at least part of a keyword hint, scoring the candidates from a current iteration and any previous iterations from previously entered terms to provide a set of possible candidates, and ordering the possible candidates based on at least the scoring. Providing incremental search suggestions may also include building compound search queries that include natural language phrases and keywords.

Abstract: Recording audio information from a meeting includes determining which audio input audio device (smartphones) correspond to which meeting participant, measuring volume levels in response to each of the meeting participants speaking, identifying one of the participants is speaking based on stored voice profiles and/or relative volume levels at each of the smartphones, recording on a first channel audio input at a first smartphone corresponding to the speaker, identifying another one of the participants is speaking based on stored voice profiles and/or relative volume levels at each of the smartphones, recording on a second channel, separate from the first channel, audio input at a second smartphone corresponding to the other speaker, and merging the first and second channels to provide a storyboard that includes audio input from the channels and identification of speakers based on which specific ones of the channels contains the audio input.