Abstract: Automatically mapping and combining the application of machine learning models to answer queries according to semantic specification. A query is parsed to extract keywords from the query and to contextualize the query. Based on the keywords, machine learning models are selected that process concepts associated with the keywords. The machine learning models are sorted according to the contextualization of the query. The machine learning models are run on multimodal data according to a sorted order, where data resulting from an output of one of the machine learning models is used as input to another one of the machine learning models. A query result is output based on a result from running the machine learning models.

Abstract: Systems and methods are described for service coordination using a PartiQL query. For instance, a method may include selecting a recipe from a plurality of recipes in response to a request from a user device, wherein the recipe includes a plurality of operations to provide a complex function, each of the plurality of operations corresponding to a service of a plurality of services; determining a PartiQL query for an operation of the plurality of operations; executing the PartiQL query to obtain a result; transmitting a call to a service of the plurality of services that corresponds to the operation based on the result; receiving a response from the service; and after all operations of the plurality of operations are called, transmitting a response to the request to the user device.

Abstract: A method and a system for automatically generating a data acquisition module are provided. The method is such that an input terminal inputs at least one piece of data to be converted, and sends the at least one piece of data to be converted to a conversion terminal. Each of the at least one piece of data to be converted includes at least one piece of identification information. The conversion terminal identifies the at least one piece of identification information to obtain an identification result. The at least one piece of data to be converted is converted into target data. A data generation end at least generates a data acquisition module based on the target data.

Abstract: Methods and systems for creating a cluster view person for genealogical studies. Methods may include obtaining a plurality of genealogical trees. Each of the genealogical trees may include a plurality of interconnected nodes representing individuals that are related to each other. Methods may also include identifying one or more of the genealogical trees that contain a similar individual. Whether two individuals are grouped may depend on similarity and/or quality thresholds. Methods may include creating an aggregate individual including each of the similar individuals in each of the identified genealogical trees. The aggregate individual may combine information from each of the similar individuals.

Abstract: A relation visualizing apparatus to an embodiment includes a memory; and a processor configured to: receive, as an input, dialog content data representing a content on which two or more persons have had a dialog with respect to predetermined two or more topic items and generate a graph, composed of nodes and edges, by using the topic items as the nodes and utterer IDs identifying persons having given utterance to two topic items different from each other as the edges, the edges connecting nodes corresponding to the two topic items; and display the generated graph.

Abstract: Systems and methods for automated content generation and delivery are provided herein. The system can include a memory that can include a content item library. The content library can include a hierarchical data structure having levels and a plurality of data packets, each of which data packets is linked with at least a portion of the hierarchical data structure. The system can include at least one server that can identify and deliver an item within a first content domain to a user device, evaluate a response to the delivered item, generate a scalar estimated skill level with a unidimensional evaluation engine, select and present a next item based on the estimated skill level, and upon completion of an assessment, generate a vector estimated skill level with a multidimensional evaluation engine.

Abstract: Systems and methods for efficiently querying distributed data are disclosed. An example method includes receiving a query from a device; transmitting the query to multiple distributed data stores; receiving, from the data stores, first data items satisfying the query; generating first-page results from the first data items; based on the first-page results, generating a first-page watermark; transmitting the first-page results and the first-page watermark to the device; receiving a second-page request from the device, the second-page request including the query and the first-page watermark; transmitting the query and at least a portion of the first-page watermark to the data stores; receiving, from the data stores, second data items satisfying the query and the portion of the first-page watermark; generating second-page results from the received second data items; and transmitting the second-page results to the device.

Abstract: This disclosure enables (1) creation of various tags and (2) tagging of various data structures identified above with such tags. Therefore, once tagged, these data structures can be processed by various application programs, without reprograming of these application programs or with minimal reprogramming of these application programs, because these tags accommodate or account for potential changes to these data structures (e.g., in format) that are made before these data structure are received for processing, as explained above. For example, some of such tags may be business user defined categorizations of data structures that can be evaluated during processing of some of such data structures and subsequently used as inputs to a standardized logic, thereby eliminating of reprogramming of these application programs or minimizing reprogramming of these application programs.

Abstract: Client data corresponding to a single client can be stored. A decision to proceed with a defragmentation of two or more particular core groups can be determined. A destination core group to receive client data can be identified. At least one additional core group can be initiated to manage interim data write requests from the single client. Each of the two or more particular core groups can be closed to data write requests. A defragmentation of the two or more particular core groups can be performed by merging into the destination core group. The destination core group can be availed to data read and delete requests. The two or more fragmented core groups can be reallocated for other uses. The additional core groups continue to receive read and write requests. The destination core groups further can be merged and defragmented further.

Abstract: Systems and methods are provided for training a machine learning model using a plurality of data related to a product and services support system to determine a plurality of parameters to be used to search for one or more results for an input stream and storing the plurality of parameters in one or more databases. Systems and methods further provide for receiving an input stream from a user computing device, parsing the input stream to generate a parsed input stream, translating the parsed input stream into one or more of the plurality of parameters output from the machine learning model to generate a search string, searching a knowledge base using the search string to determine one or more results associated with the parsed input stream, and providing at least one result of the one or more results associated with the parsed input stream to the user computing device.

Abstract: A data processing method according to an embodiment acquires data including a plurality of records, divides the data based on external condition identification information such as a user ID to generate data sets Di for respective external conditions, divides each of the data sets Di based on label information indicating whether the record corresponds to a positive label indicating that a predetermined event has occurred or a negative label indicating that the predetermined event has not occurred to generate two data sets Di+ and Di? for the respective label information, generates difference data for a combination of a record included in one data set of the two data sets and a record included in the other data set, combines the generated difference data to generate integrated data Dnew, performs statistical analysis using Dnew, and outputs a result of performing the statistical analysis.

Abstract: A query scheme is presented in which a query filter data structure is created and utilized to determine whether to obtain live query data from a storage server or aged data within an associated dataset. The number of queries to the storage server may be reduced and overall efficiency of the query system is increased. Another query scheme is presented to adjust the frequency of a dataset refresh based upon a user defined data age parameter indication that is contained a subsequent query and/or based upon whether a frequency of storage server queries is above a predetermined threshold. The propensity of obtaining query results from a dataset is increased while the propensity of queries to the storage server decreases, thereby increasing query system efficiency.

Abstract: A computer-implemented system and method for planning recurring events is provided. Event objects for events are stored in a database. A trigger notifying the beginning of an event is received and an event object representing the event is generated in response to the trigger. An event class is associated with a set of parameters and is assigned to the event object. A set of activity data is created for the event object and each activity data includes structured and unstructured data describing an event activity occurred during the event. At least one event object is retrieved from the database as a model and the parameter values of the model event object are displayed. At least one of the parameter values of the model event object is modified and the modification is reflected against other parameter values of the model event object that are dependent on the modified parameter value.

Abstract: A computer implemented method transforms data. Responsive to receiving a data transformation of an input string to an output string, a computer system identifies mappable tokens in the input string that are mappable to the output string. The computer system creates a set of initial mappings for a set of common tokens in the mappable tokens. The set of initial mappings maps the set of common tokens from the input string to the output string. The computer system creates a set of user mappings that maps the mappable tokens from input string to the output string using a user input to the set of initial mappings. The computer system generates program code that transform input strings to output strings using the set of user mappings that maps the mappable tokens from input string to the output string, wherein the program code is used to transform input strings to output strings.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for correcting entity names. One method includes receiving texts and deriving a plurality of name-context pairs from the texts. The method further includes calculating a context consistency measure for each name-context pair and storing context-entity name data representing the name-context pairs. Another method includes identifying an entity name and one or more context terms from a query and generating candidate names for the entity name. The method further includes determining a score for each of the candidate names, selecting a number of top scoring candidate names, and using the selected candidate names to respond to the query.

Abstract: An example method for filesystem pass-through on lightweight virtual machine containers includes executing a container on a host, and creating a file system overlay in a local file system storage located on the host. The example method further includes copying files and directories into the file system overlay from a shared file system until the file system overlay is fully populated. The file system overlay is fully populated when all the files and directories from the shared file system are copied into the file system overlay. Once fully populated, completion is marked which indicates the file system overlay is fully populated, where marking the completion prevents accessing a read-only base image within the shared file system.

Abstract: The present invention provides a method and system for storing and retrieving tags. Each tag is associated with a resource, upon a user's request. A tagging GUI is displayed which presents the available tags for one particular resource and/or a tag cloud GUI is displayed which presents tags for more than one resource. The tagging GUI allows to assign new tags to single resources. The tag cloud GUI enables users to search for resources which have been assigned certain tags. In the tag cloud GUI the relevancy of each single tag is visually reflected by its weighting factor which is determined by the frequency of occurrence.

Abstract: A system and a method for identifying and ranking agents are disclosed herein. The system includes an analytics engine which retrieves information from external and internal databases. The analytics engine uses the information retrieved from these databases, in addition to one or more success factors or key attributes, to identify and rank prospective agents. The analytics engine can also match one or more prospective agents with a general agent and provide ranking and performance assessment reports for evaluating and following up on the agent’s career development.

Abstract: Described herein is a system that processes personal data in databases. The system samples data stored in columns of data tables and analyzes the sampled data to determine whether the sampled data includes personal data. Based on the analysis, the system marks which data tables and which columns of the data tables store personal data. The system receives a request to process personal data for a subject. From data tables that are marked as storing personal data, the system identifies records storing personal data for the subject. The system additionally identifies other data tables marked as storing personal data that reference or are referenced by the data tables including the records referencing the subject. The system processes the data stored in the columns that are marked as storing personal data.

Abstract: Techniques and architectures for data ingestion in an environment having a distributed data storage system. A request to import data into the environment. The data to be imported from an external source through an application programming interface (API). The request is analyzed to determine if the request corresponds to a request to import a large data load. The data is staged if the request is for the large data load. Data management jobs are created to cause the data to be stored in one or more nodes of the distributed data storage system. The data management jobs are transmitted to corresponding nodes in the distributed data storage system. The jobs are executed asynchronously to cause the data to be stored in the nodes.