Abstract: A method, system, and computer program product for a data modelling platform to engage with a user via a user interface is provided. A predictive data model is displayed based on the user query. Provenance and evidence is provided based on a user selected result. The ground truth dataset is modified in response to receiving a user action via the user interface.

Abstract: Techniques are described herein for managing data structure groups. Such techniques may include providing to a data structure group, by a reader, a plurality of data structure identifiers including a first data structure identifier and a second data structure identifier; mounting, by the data structure group, a first data structure identified by the first data structure identifier and including a first instance identifier; mounting, by the data structure group, a second data structure identified by the second data structure identifier and including a second instance identifier; making a first determination that the first data structure and the second data structure are mounted; making a second determination that the first instance identifier and the second instance identifier match; and marking, based on the first determination and the second determination, the data structure group as ready-to-read.

Abstract: The described technology is generally directed towards causing the generation of a content selection graph (or set of graphs) upon receipt of a notification that a new graph or replacement graph is needed with respect to a starting timepoint. For a new graph, a timepoint for that new graph indicates the need for the new graph at a given starting time. For a replacement graph, a notification (subscribed from a monitoring service) can indicate that an existing graph has changed; a replacement graph is generated with a graph identifier of the replacement graph, which then replaces the graph identifier of the existing graph in the mappings of valid graphs to start times. A Redis cache can be used to maintain the various graph sets, including the active graph sets and graph sets that will become active at a future time.

Abstract: A user identifier is obtained and an attribute identifier and an attribute value of at least one personal attribute corresponding to the user identifier is obtained. A target attribute correspondence to each personal attribute of the at least one personal attribute is generated based on the attribute identifier and the attribute value of the personal attribute. A determination is performed as to whether a target attribute storage field corresponding to the user identifier exists in stored first correspondences between one or more user identifiers and one or more attribute storage fields. When the target attribute storage field exists in the stored first correspondences, the target attribute correspondences are stored in the target attribute storage field.

Abstract: A computer-implemented method includes: receiving, by a computing device, a database-level auto_purge value for a database having a plurality of tables, wherein the database-level auto_purge value represents a value associated with the entire database for when data is set to be purged or deleted from the plurality of tables in the database; setting, by the computing device, the database-level auto_purge value for the database; setting, by the computing device, table-level auto_purge values for the plurality of tables included in the database based on the database-level auto_purge value; and automatically purging data in the plurality of tables based on the table-level auto_purge values.

Abstract: Discussed are various embodiments of a system and a method of managing a standard component, and more particularly, a system and a method of managing a standard component, which are capable of periodically updating a plurality of standard components in order to intensively use a small number of good components in a component group including a plurality of standard components, and measuring and managing a number of the plurality of standard components.

Abstract: A view gateway is configured to receive a first query in a first programming language from a client. The view gateway is configured to select a template from a plurality of templates. A view gateway is configured to compile the first query and the selected template into a second query. A view gateway is configured to send the second query to a data store for processing. A view gateway is configured to receive a query result that is responsive to the second query; and send the query result to the client.

Abstract: It is provided an information linkage system, which is configured to allow a plurality of organizations to register and update data, and is formed of a computer including: a calculation device configured to execute predetermined calculation processing, to thereby implement the following functional modules; and a storage device accessible to the calculation device, the information linkage system comprising: an information linkage control module configured to receive a registration request for data, an update request for data, and an acquisition request for data from a plurality of external systems; an information linkage database in which data is allowed to be registered and updated; an information linkage database access module configured to access the information linkage database in response to a request received by the information linkage control module; and a reliability calculation module configured to calculate reliability information relating to the data stored in the information linkage database.

Abstract: A platform for implementing a method of aggregating and contextualizing metrics relevant to developing, launching and marketing a target therapeutic or related therapy. The method of processing the metrics includes retrieving data related to the target from one or more data sources and synthesizing the retrieved target data in a contextual manner and creating synthesized target data by converting unstructured data into structured data including an event, wherein an event comprises a corpus of data from a single source on a single date. The synthesized target data is stored in a target specific database and a user may query the database regarding the target, where the query includes at least one search parameter. The user query is processed against the synthesized target data in the target specific database and the results are presented to the user.

Abstract: Method and systems for generating an adjacency matrix A and a directional relation graph representing a relationship between one or more diagnostics. The adjacency matrix with all zero's is initialized. One or more entries in the adjacency matrix A are revised by, for each source diagnostic s, decreasing a corresponding count A(s,d) in the adjacency matrix A to decrease a corresponding directional relation in response to the diagnostic s failing and one or more other diagnostics d passing; increasing the corresponding count A(s,d) in the adjacency matrix A to increase the corresponding directional relation in response to the diagnostic s failing and one or more other diagnostics d failing; and maintaining a current value of the corresponding count A(s,d) in the adjacency matrix A in response to the diagnostic s passing or having no corresponding data. The directional relation graph is generated based on the adjacency matrix A.

Abstract: A recommendation engine for works of literature uses patterns of flow and element similarities for scoring a first user-rated work of literature against one or more recommendation candidate works of literature. Cluster models are created using meta-data modeling the works of literature, the meta-data having literary element categories and instances within each category. Each instance is described by an index value (position in the literature) and significance value (e.g. weight or significance). Cluster finding process(es) invoked for each instance in each category find Similarity Concept clusters and Consistency Trend clusters, which are recorded into the cluster models representing each work of literature. The cluster model can be printed or displayed so that a user can visually understand the ebb and flow of each literary element in the literature, and may be digitally compared to other cluster models of other works of literature for potential recommendation to a user.

Abstract: Techniques for using online user activity in determining relevance of attributes to improve computer functionality in generating recommendations of online content are disclosed herein. In some embodiments, a computer system calculates a corresponding relevance score for each attribute of a user based on a total number of online postings for which the user has performed at least one of a plurality of online actions within a particular sliding window of time defining a most recent time period, an attribute activity number representing a number of online postings in the plurality of online postings that have the attribute, and an inverse of a frequency value representing how many of a total number of online postings published within the particular sliding window of time have the attribute. In some embodiments, the computer system causes at least one recommendation associated with the user to be displayed based on the calculated relevance scores.

Abstract: A method includes receiving, by a computer system configured to generate search result, a query, identifying a plurality of entities in the query, determining, using a knowledge graph, a measure of a relationship between the entities in the query, identifying a replacement entity for a first entity of the entities in the query, wherein the replacement entity is determined to improve the measure of the relationship between the entities when the first entity is replaced by the replacement entity, and generating a search result using the query modified by the replacement entity, which replaces the first entity in the query.

Abstract: Aspects of the subject disclosure may include, for example, a method including enabling, by a system comprising a processor, a first modification of a first user profile at a secondary data repository of a communication network; the first modification is directed by a first application operating at a first communication device of the communication network. A usage event is identified that is associated with the first communication device according to the first modification to the first user profile. A second modification to a second user profile is replicated at a primary data repository according to a change in operation of a second application associated with the usage event that is identified to the first communication device; the replication is performed according to an update policy for the primary data repository. Other embodiments are disclosed.

Abstract: Methods, computer program products, and systems are presented. The methods include, for instance: metadata on respective datasets from a plurality of data sources. An enhanced metadata is prepared with semantic information, available data statistics, and search index associated with items of the metadata. The metadata is also classified based on ontology rules. An intent phrase to search the datasets from the plurality of data sources is obtained from a user. The enhanced metadata is searched with a semantic search query formed from the intent phrase, and search result is classified into semantic element classes generated from the intent phrase. A metadata model that satisfies the intent phrase is produced by identifying join columns and respective join relationships from the search result.

Abstract: Ephemeral stories allow users of an online system, such as a social networking system, to share content for a pre-determined temporary length of time. Channels group and organize stories based on content. Topic-based channels allow contain stories that have related content. Hashtag- and sticker-associated channels contain stories that include particular hashtags or stickers, respectively. User-specific channels contain content tailored by the online system for display to a particular user based on preferences and history. Collaborative channels are channels that are private to a specific group of users. The use of channels improves the online experience by grouping stories by content, thereby facilitating users' interaction with similar content.

Abstract: A method for tracking actions performed in association with a data set includes identifying multiple sources of historical information describing actions performed on the data set. The method periodically gathers this historical information from the multiple sources and compiles the historical information in a centralized repository. In certain embodiments, the method stores the historical information in the form of individual records associated with the data set. In the event any actions performed on the data set are the result of policies established for the data set, the method determines the policies associated with the actions where possible. The method includes these policies with the historical information in the centralized repository. A corresponding system and computer program product are also disclosed.

Abstract: A computer-implemented method according to one embodiment includes identifying at a pre-allocation module a size of object data to be stored within a storage node, identifying at the pre-allocation module file system parameters associated with the storage node, calculating at the pre-allocation module pre-allocated details needed for storing the object data within the storage node, utilizing the size of the object data and the file system parameters associated with the storage node, and sending the object data and the pre-allocated details from the pre-allocation module to the storage node.

Abstract: A recommendation engine for works of literature uses patterns of flow and element similarities for scoring a first user-rated work of literature against one or more recommendation candidate works of literature. Cluster models are created using meta-data modeling the works of literature, the meta-data having literary element categories and instances within each category. Each instance is described by an index value (position in the literature) and significance value (e.g. weight or significance). Cluster finding process(es) invoked for each instance in each category find Similarity Concept clusters and Consistency Trend clusters, which are recorded into the cluster models representing each work of literature. The cluster model can be printed or displayed so that a user can visually understand the ebb and flow of each literary element in the literature, and may be digitally compared to other cluster models of other works of literature for potential recommendation to a user.

Abstract: Systems, methods, and non-transitory computer-readable media can determine a set of potential visualizations for a data set based on a set of visualization templates. The set of potential visualizations is ranked based on ranking criteria. A set of visualization recommendations for the data set is determined based on the ranking.