Abstract: A method for ranking comments includes receiving a request for a media item; obtaining a plurality of comments associated with the media item; and for each of the plurality of comments, identifying an entity that provided a respective comment; and identifying an attribution score for the entity, the attribution score based on a quantity of responses attributed to a sharing message pertaining to the media item, the responses representing consumption of the media item. The method further includes determining ranking scores for the plurality of comments based on corresponding attribution scores; and providing the media item and at least a portion of the plurality of comments to be displayed in an order defined by the ranking scores.

Abstract: An approach is provided to identify permanence data corresponding to terms included in a corpus of a question answering (QA) system. Based on the identified permanence, a time-based confidence of each of the terms is established. Terms are identified as a plurality of candidate answers to a question posed to the QA system. Each of the plurality of candidate answers are scored with the scoring being at least partially based on the time-based confidence established for each of the terms.

Abstract: An automated creation of a summary video based on video segments extracted from several videos by using a social network of viewers and a social curve specified by a user in order to select and order the video segments. A social network of viewers (influence scores, experts) may be used to establish metrics for video segments. A social curve may be defined with respect to the video segment metrics to allow for the automatic creation of a summary video.

Abstract: A system for reuse of content within documents can include storage media on which a document graph is stored, and labeler software that, when executed by a processing system, directs the processing system to at least: aggregate, for a window of time, a plurality of actions carried out by a user on content associated with a document within a productivity application; normalize the plurality of actions into at least one predefined action class; determine a label of the user in relation to the document or a portion of the content associated with the document based on the at least one predefined action class; and store the label associated with the user and the document or the portion of the content in a document graph. A search of the document graph for reusable content can then be directed to related content associated with a user having a particular label.

Abstract: A method, system, and processor-readable storage medium are directed towards generating a report derived from data, such as event data, stored on a plurality of distributed nodes. In one embodiment the analysis is generated using a “divide and conquer” algorithm, such that each distributed node analyzes locally stored event data while an aggregating node combines these analysis results to generate the report. In one embodiment, each distributed node also transmits a list of event data references associated with the analysis result to the aggregating node. The aggregating node may then generate a global ordered list of data references based on the list of event data references received from each distributed node. Subsequently, in response to a user selection of a range of global event data, the report may dynamically retrieve event data from one or more distributed nodes for display according to the global order.

Abstract: A video search apparatus includes a storing unit, an input unit, and a search unit. The storing unit stores video data along with video attributes information indicating, for each concept, a confidence score that the concept is included in the video data. The input unit inputs, as preference information, a coefficient of each concept which is desired to be included in video to be searched for and a coefficient of a superordinate concept of the concept which is desired to be included in the video to be searched for. The search unit searches for, based on the preference information input by the input unit, video that matches the preference information from among the video data stored in the storing unit.

Abstract: An approach is provided to identify permanence data corresponding to terms included in a corpus of a question answering (QA) system. Based on the identified permanence, a time-based confidence of each of the terms is established. Terms are identified as a plurality of candidate answers to a question posed to the QA system. Each of the plurality of candidate answers are scored with the scoring being at least partially based on the time-based confidence established for each of the terms.

Abstract: Systems and methods for accounting for data whose rebuilding is deferred in a dispersed storage network. The methods include determining a number of compromised slices associated with a dispersed storage unit. The number of existing slices associated with the dispersed storage unit is also determined. A comparison of the number of compromised slices plus the number of existing slices associated with the dispersed storage unit, to a storage capacity, is performed in order to produce a capacity determination. Write requests directed towards the dispersed storage unit may be failed based on the capacity determination. For example, the DS unit may fail write requests, when a write request would cause the dispersed storage unit to exceed the storage capacity of the dispersed storage unit when taking into consideration existing slices as well as compromised slices that need to be rebuilt.

Abstract: Systems, methods, and non-transitory computer-readable media can acquire a set of labels associated with a set of content items. Each label in the set of labels can be associated with at least one content item in the set of content items. It can be determined that at least two labels, out of the set of labels, are related. The at least two labels can be determined to be related based on at least one of a co-occurrence metric associated with the at least two labels or a topic similarity metric associated with the at least two labels. One label can be selected, out of the at least two labels, as being representative of the at least two labels.

Abstract: Techniques are disclosed for identifying the same online user across different communication networks, and further creating a unified profile for that user. The unified profile is an aggregation of publicly available user profile attributes across the different networks. In an embodiment, the techniques are implemented as a computer implemented methodology, including: (1) feature space analysis to identify relevant user features that allows for clusterization of the given target network(s), (2) unsupervised candidate selection to identify one or more candidate user profiles from each target network and that are likely belonging to a target user or so-called queried user, and (3) supervised user identification to identify a likely matching user profile for that target user from each target network. A unified user profile can then be built from data taken from all matched user profiles, and effectively allows a marketer to better understand that user and hence execute more informed targeting.

Abstract: As disclosed herein a computer-implemented method includes receiving a delta scan from an endpoint system comprising changes to a baseline inventory, and determining if the delta scan can be processed. The method further includes responsive to determining that the delta scan can be processed, processing the delta scan to produce a synchronized baseline inventory, and responsive to determining that the delta scan cannot be processed, indicating that the delta scan is unable to be processed. The method further includes responsive to indicating the delta scan is unable to be processed, receiving a most recent full system scan from the endpoint system to provide a new synchronized baseline inventory. A computer program product and a computer system corresponding to the above method are also disclosed herein.

Abstract: A method for document similarity analysis. The method includes obtaining a document to be archived, and identifying a document category similar to the document to be archived. The similar document category is identified by: identifying a document category that includes indexing terms that are identical to indexing terms in the document to be archived, obtaining term frequency vectors for the identical indexing terms in the document to be archived and in the identified document category, generating normalized term frequency vectors, from the term frequency vectors, calculating a common denominator similarity based on the normalized term frequency vectors and a common denominator, and determining that the document category is similar to the document to be archived based on the common denominator similarity. The method further includes registering the document to be archived in the document category.

Abstract: Embodiments provide a system and method for semantic distance calculation. The method can involve receiving a plurality of documents having a set of subjects extracted through the use of latent dirichlet allocation; for each document in the plurality of documents, generating a classification list comprising a ranking of the one or more subjects based on the relevance of each subject to the document; for each classification list, calculating the semantic distance between each subject present on the classification list; aggregating the plurality of classification lists; and creating a distance matrix containing the relative semantic distances between each member of the set of subjects.

Abstract: Embodiments of the present disclosure may be utilized to analyze a content item comprising text to identity: a quote, a named entity that is the source of the quote (e.g., a person or organization such as a company), and identification information for the named entity (such as a title of the person giving the quote). Quotes may also be ranked to determine, for example, the best quotes to include in an article.

Abstract: Embodiments provide a system and method for semantic distance calculation. The method can involve ingesting a plurality of documents; extracting a set of subjects from the plurality of documents using latent dirichlet allocation; for each document in the plurality of documents, generating a classification list comprising a ranking of the one or more subjects based on the relevance of each subject to the document; for each classification list, calculating the semantic distance between each subject present on the classification list; aggregating the plurality of classification lists; and creating a distance matrix containing the relative semantic distances between each member of the set of subjects.

Abstract: A system extracts data from one or more sources of data and displays information regarding the data using interactive visualizations that allow a user to interact directly with the visualizations of the data, without necessarily requiring the user to utilize a menu-driven interface.

Abstract: A display structure that includes data items mapped based on relationships among the data items is visually presented on a user interface. The displayed data includes blocks of data received over a block data interface. The display structure may include a first portion indicative of availability of multiple 2-dimensional views of the data items and a second portion for the user to select one of the multiple 2-dimensional views to become an active view that is viewable by the user.

Abstract: A method and a device for inquiring a map are provided. The method includes receiving a query statement inputted by a user; performing a word segmentation on the query statement received to obtain a result of the word segmentation; extracting specific information related to a demand of the user from the result of the word segmentation; inquiring a route and/or a point of interest related to the specific information extracted in a map.

Abstract: Methods and apparatuses for providing a k-nearest neighbor for location based services are provided. A method can include querying a database to detect a plurality of interest points within a predetermined distance of the user device using a kNN algorithm, organizing the interest points within a Voronoi tree, and continuously return a position specific result of relevant interest points.

Abstract: One or more processors initiate generation of an identifier based on the definitions of both a primary range and a secondary range. One or more processors obtain a unique sequence value from a unique sequence range of known maximum number of values. One or more processors calculate an offset value based on, at least in part, the primary range and the secondary range. One or more processors add the offset value to the unique sequence value to generate an identifier value.