A system and method for visualizing and querying high dimensional data to a user. The system includes a user device, a data-pearls visualization and querying server. The server obtains the high dimensional data from the user device associated with user. The server generates data clusters and sub-divides the data clusters into non-overlapping subsets of data-pearls using a clustering technique. The server selects a shape for each data-pearl by comparing a distance between centroid of a data-pearl and a farthest point from a determined centroid using L.sub.p norm distance measures. The server configures each data-pearl in a three-dimensional plot. The server enables the user to visualize the data-pearls on a screen of the user device. The server queries data based on a query using data dimension technique. The server dimensions data related to the query through determined classifiers based on filtered data after pruning unrelated data to the query.

Systems and methods for conversational user experiences and conversational database analysis disclosed herein improve the efficiency and accessibility of low-latency database analytics. The method may include obtaining data expressing a usage intent with respect to the low-latency database analysis system, wherein the data expressing the usage intent includes a current request string expressed in a natural language, a current context associated with the current request string, and a previously generated context associated with a previously generated resolved-request, identifying, from the current request string, a conversational phrase corresponding to a conversational phrase pattern from a defined set of conversational phrase patterns, generating a resolved-request based on the identified conversational phrase, including the resolved-request in the current context, obtaining results data responsive to the resolved-request from a distributed in-memory database, generating a response including the results data and the current context, and outputting the response.

Methods are presented for providing dynamic search filter suggestions that are updated and ranked based on the user filter selections. One method includes detecting a query received in a user interface (UI), calculating, by a search-candidate model, first search results, and calculating, by a suggestions model, first filter suggestions for filter categories to filter responses to the query. The suggestions model is obtained by training a machine-learning algorithm utilizing pairwise learning-to-rank modeling. The first search results and the first filter suggestions are presented in the UI. When a selection in the UI of a filter suggestion is detected, the search-candidate model calculates second search results for the filter categories based on the query and the selected filter suggestion, and the suggestions model calculates second first filter suggestions based on the query and the selected filter suggestion. The second search results and the second filter suggestions are presented in the UI.

Systems and methods for querying a database are disclosed. A server computing device includes a processor and a memory storing instructions that, when executed by the processor, cause the server computing device to: receive a query input from a client device over a network connection; establish a non-blocking socket between the client computing device and the server computing device; generate a database query based on the query input; cause the database query to begin executing against one or more databases; perform a read request on the non-blocking socket; receive a code in response to the read request on the non-blocking socket; determine whether the network connection exists between the client device and the server device based on the received code; and cause the database query to be cancelled when the server determines that the network connection does not exist between the client device and the server device.

A sequence of context based search verb and search terms are selected via either touch or voice selection in a mobile wireless device and then a human articulated voice query is expanded using a culture and a world intelligence dictionary for conducting more efficient searches. Focus groups are used for populating prior query search databases for storage in the mobile wireless device that are organized by context based search terms in a mobile wireless device for efficient search.

Visualization of a cohort for high-dimensional categorical data is disclosed. One example is a system including a display module to identify real-time selection of a query data element in an interactive visual representation of high-dimensional categorical data elements comprising a plurality of categorical components. A matrix generator generates a binary distance matrix with columns representing categorical components, and entries in a row indicative of a degree of similarity of respective categorical components of the selected query data element to a data element represented by the row, and determines a category weighting matrix by associating a weight with entries in each column of the binary distance matrix. An evaluator evaluates a weighted similarity score for a data element represented by a row of the category weighting matrix based on entries of the row. A selector iteratively and interactively selects, based on weighted similarity scores, a cohort of categorical data elements.

A database security system protects a data table at both the column level and the individual data record level. Access to data records within the data table is governed by categories assigned to data records, by user roles assigned to users, and by a set of security access tables. A first access table maps data record identifiers to data record categories, data record protection schemes, and corresponding scheme keys. A second access table maps user roles to data record categories. A third access table maps column identifiers to column protection schemes and corresponding scheme keys. A fourth access table maps user roles to column identifiers. If a user requests access to a data record, the security access tables are queried using the data record identifier, the associated column identifier, and the user roles associated with the user to determine if the user can access the requested data record.

A technique includes modifying a first record based on a plurality of training records to provide a plurality of modified records. The plurality of training records are associated with a regression model, and a target outcome is associated with the first record. The technique includes applying the regression model to the plurality of modified records to provide outcomes for the modified records; and selecting a group of the modified records based at least in part on the outcomes for the modified records. The technique includes providing a recommendation for the first record to change an outcome predicted for the first record by the regression model based at least part on the target outcome and the outcomes for the modified records.

Systems and methods are provided for managing and accessing data using one or more data cloud servers. An exemplary method includes: receiving from one or more data sources, a first data set; stratifying the first data set into first samples; receiving from second one or more data sources, a second data set; stratifying the second data set into second samples; computing a projection factor for each of the second samples using the first samples; computing projected samples using the projection factor for each of the second samples; receiving from third one or more data sources, a third data set; computing a parameter using the third data set; selecting one or more of the projected samples to form a fourth data set; and performing a computer operation for estimating the data using the fourth data set and the parameter.

Methods and systems are disclosed for data retrieval, from databases to clients, in an environment requiring runtime authorization. In response to a request for T data records, a learning module provides a prediction R of a suitable number of data records to retrieve from a database. Following retrieval of R records or record identifiers, authorization is sought from an authorization service, resulting in A of the records being authorized. The A authorized records are returned to the requesting client, and, if more records are needed, T is decremented and the cycle is repeated. A performance notification is provided to the learning module for training, with respect to providing values of prediction R. The performance notification can be based on a measure of authorization service performance, the number A of authorized records, latency, communication or resource costs, a measure of resource congestion, or other parameters. Variants are disclosed.