Abstract: Queries that reference materialized views may be rewritten to compensate for stale materialized views. A query may be received that references a materialized view. A determination may be made as to whether the materialized view is stale. For a stale materialized view, the query may be rewritten to generate a query plan that obtains changes made to base tables for the materialized view not included in the stale materialized view and considers the change(s) when generating a result for the query from the materialized view. The rewritten query may then be performed to provide a result as if the materialized view were up-to-date.

Abstract: Using a graph representation of join history may be performed to distribute database data. Join history may be collected, captured, or tracked which describes the history of join operations between columns of different tables in a database. A graph representation of the join history may be generated. The graph representation may indicate a likelihood of different joins that may be performed between the columns of the tables of a database. An evaluation of the join history may be performed to identify columns for tables in the database to distribute the data of the tables amongst multiple storage locations according to the identified columns.

Abstract: Devices and techniques are generally described for fraud detection. A machine learning model is used to determine a first fraud risk score for a first transaction. The machine learning model includes a first set of weights. A first covariance matrix is determined for the machine learning model based at least in part on the first fraud risk score. A second set of weights for the machine learning model is determined. The second set of weights is determined based on the first set of weights and the first covariance matrix. In various examples, the machine learning model with the second set of weights is used to determine a second fraud risk score for a second transaction. A fraud decision surface is determined and the second fraud risk score is compared to the fraud decision surface. Data indicating that the second transaction is fraudulent is sent to a computing device.

Abstract: An improved user interface in which related items are grouped intuitively, and ultimately results in the number of navigational steps performed by the user to identify desired related items being reduced, is described herein. For example, instead of having a user interface display a single view that includes all related items, a recommendation system groups the related items based on their respective attribute values and produces data that results in a user interface that displays the related items in these groups. The recommendation system generates labels for these groups such that a user can clearly identify what types of related items are included therein. Thus, a user would not have to browse through a single list of related items ordered in an unfamiliar manner. Rather, a user can browse through smaller subsets of related items, and only in those groups that correspond with attribute values of interest to the user.

Abstract: What is disclosed is a method of operating a communication network, where the communication network comprises a set of users. The method includes obtaining usage activity for each of the users of the set and processing the usage activity to determine connectivity information between individual ones of the users of the set. The method also includes processing the connectivity information to determine users of the set with similar connectivity, and processing the users of the set with similar connectivity to identify a community of users within the users of the set with similar connectivity. The method also includes monitoring at least one of the users in the community to determine if action is needed for at least another one of the users in the community.

Abstract: A method and system for graph mining direction-aware proximity measurements. A directed graph includes nodes and directed edges connecting the nodes. A direction-aware proximity measurement is calculated from a first node to a second node or from a first group of nodes to a second group of nodes. The direction-aware proximity measurement from a first node to second node is based on an escape probability from the first node to the second node. Disclosed herein are methods for efficiently calculating one or multiple direction-aware proximity measurements. The direction-aware proximity measurements can be used in performing various graph mining applications.

Abstract: An auditing framework for determining whether a database disclosure of information adhered to its data disclosure policies. Users formulate audit expressions to specify the (sensitive) data subject to disclosure review. An audit component accepts audit expressions and returns all queries (deemed “suspicious”) that accessed the specified data during their execution.

Abstract: A method and system for graph mining direction-aware proximity measurements. A directed graph includes nodes and directed edges connecting the nodes. A direction-aware proximity measurement is calculated from a first node to a second node or from a first group of nodes to a second group of nodes. The direction-aware proximity measurement from a first node to second node is based on an escape probability from the first node to the second node. Disclosed herein are methods for efficiently calculating one or multiple direction-aware proximity measurements. The direction-aware proximity measurements can be used in performing various graph mining applications.

Abstract: An auditing framework for determining whether a database disclosure of information adhered to its data disclosure policies. Users formulate audit expressions to specify the (sensitive) data subject to disclosure review. An audit component accepts audit expressions and returns all queries (deemed “suspicious”) that accessed the specified data during their execution.

Abstract: An optimal path selection system extracts a connection subgraph in real time from an undirected, edge-weighted graph such as a social network that best captures the connections between two nodes of the graph. The system models the undirected, edge-weighted graph as an electrical circuit and solves for a relationship between two nodes in the undirected edge-weighted graph based on electrical analogues in the electric graph model. The system optionally accelerates the computations to produce approximate, high-quality connection subgraphs in real time on very large (disk resident) graphs. The connection subgraph is constrained to the integer budget that comprises a first node, a second node and a collection of paths from the first node to the second node that maximizes a “goodness” function g(H). The goodness function g(H) is tailored to capture salient aspects of a relationship between the first node and the second node.

Abstract: A dimensionality reduction method of generating a reduced dimension matrix data set Dnew of dimension m×k from an original matrix data set D of dimension m×k wherein n>k. The method selects a subset of k columns from a set of n columns in the original data set D where the m rows correspond to observations Ri where i=1, . . . , m and the n columns correspond to attributes Aj where j=1, . . . , n and dij is the data value associated with observation Ri and attribute Aj. The data values in the reduced data set Dnew for each of the selected k attributes is identical to the data values of the corresponding attributes in the original data set.

Abstract: A dimensionality reduction method of generating a reduced dimension matrix data set Dnew of dimension m×k from an original matrix data set D of dimension m×k wherein n>k. The method selects a subset of k columns from a set of n columns in the original data set D where the m rows correspond to observations Ri where i=1, . . . , m and the n columns correspond to attributes Aj where j=1, . . . , n and dij is the data value associated with observation Ri and attribute Aj. The data values in the reduced data set Dnew for each of the selected k attributes is identical to the data values of the corresponding attributes in the original data set.

Abstract: The invention concerns a method for estimating characteristic information of data items in a data set, such as a database, based on parameters of a multifractal distribution. The invention facilitates efficient estimation of such characteristic information of data contained in a data set more accurately than known estimation methods and without requiring an exhaustive analysis of the data. The invention also concerns an efficient technique for generating the parameters for the multifractal distribution.