A method for searching data includes storing a probe data and a target data expressed in a first orthogonal domain. The target data includes potential probe match data each characterized by the length of the target data. The probe data representation and the target data are transformed into an orthogonal domain. In the orthogonal domain, the target data is encoded with modulation functions to produce a plurality of encoded target data, each of the modulation functions having a position index corresponding to one of the potential probe match data. The plurality of encoded target data is interfered with the probe data in the orthogonal domain and an inverse transform result is obtained. If the inverse transform result exceeds a threshold, information is output indicating a match between the probe data and a corresponding one of the potential probe match data.

Techniques disclosed herein relate generally to evaluating and selecting candidate datasets for use by software applications, such as selecting candidate datasets for training machine-learning models used in software applications. Various machine-learning and other data science techniques are used to identify unique entities in a candidate dataset that are likely to be part of target entities for a software application. A merit attribute is then determined for the candidate dataset based on the number of unique entities that are likely to be part of the target entities, and weights associated with these unique entities. The merit attribute is used to identify the most efficient or most cost-effective candidate dataset for the software application.

A system for updating a hypercube includes an interface and a processor. The interface is configured to receive an indication to update a cell of the hypercube. The processor is configured to determine a primary dimension value associated with the cell; determine a group of dependencies based at least in part on the primary dimension value, wherein a dependency of the group of dependencies comprises one or more primary dimension values and a pattern; for the dependency of the group of dependencies, determine a set of source locations based at least in part on the one or more primary dimension values and the pattern; and mark the set of source locations as invalid.

Methods for generating data models using a generative adversarial network can begin by receiving a data model generation request by a model optimizer from an interface. The model optimizer can provision computing resources with a data model. As a further step, a synthetic dataset for training the data model can be generated using a generative network of a generative adversarial network, the generative network trained to generate output data differing at least a predetermined amount from a reference dataset according to a similarity metric. The computing resources can train the data model using the synthetic dataset. The model optimizer can evaluate performance criteria of the data model and, based on the evaluation of the performance criteria of the data model, store the data model and metadata of the data model in a model storage. The data model can then be used to process production data.

A system, program product, and method for enhancing automatic multidimensional query processing. The method includes executing a database query including semi-joining a plurality of dimension tables with a fact table. The method also includes identifying for extraction one or more data values from each dimension table of the plurality of dimension tables. The data values from each dimension table of the plurality of dimension tables are associated with a respective record identification (RID), thereby defining one or more RIDs. The method further includes generating a plurality of RID lists. Each RID list of the plurality of RID lists includes a collection of the one or more RIDs for the respective dimension table. The method also includes merging the plurality of RID lists, sorting, subject to the merging, the plurality of RIDs as a function of data location, and fetching the data values from the fact table.

Computing systems, database systems, and related methods are provided for managing data pertaining to electronic messages. A database system includes a database including a first object having a plurality of content fields corresponding to a first instance of an electronic message configured for a first communication channel and a server coupled to the database and a network to create a second database object corresponding to a second instance of the electronic message configured for a different communication channel, create a multichannel data structure in the database maintaining an association between the first and second objects, automatically populate a subset of content fields of the second object with values copied from the first object based on a mapping between the two communication channels, and thereafter use the second object to generate a version of the electronic message to be communicated to a recipient using the second communication channel.

A system for efficiently parsing semi-structured deep packet inspection traffic data tied to a telecommunications entity. The system comprises a computing device having access to a user activity data source and is configured to progressively accumulate a plurality of incoming usage activity data into a plurality of hypercubes, classify streaming data on-the-fly into multiple grades, route it to an appropriate next stage of processing, numerically factorize it to enable drilldown to individual subscriber data, and organize into layouts for efficient data processing, anomaly detection, and subsequent access/investigation. A computerized method for performing the same.

Systems, devices, computer-implemented methods, and tangible non-transitory computer readable media for performing multilayered generation and processing of computer instructions are provided. For example, a computing device may receive a request with instructions in a first computer language, parse the instructions in the first computer language, analyze the instructions in the first computer language in view of information describing structure of a first application, generate instructions in a second computer language different from the first computer language where the instructions in the second computer language are generated based on the instructions in the first computer language and the information describing structure of the first application, obtain a result from a second application where the result comprises information based on the instructions in the second computing language, and provide the result in response to the request comprising the instructions in the first computer language.

A method may include generating, based on a representation of a hierarchy stored in a database, a visiting sequence data structure. The hierarchy may be stored in a table in the database. Each of a plurality of rows comprising the table may correspond to one of a plurality of nodes comprising the hierarchy. The visiting sequence data structure may include a row vector specifying an order for traversing the plurality of nodes in the hierarchy. A hierarchical window function may be executed by iterating through the plurality of rows in the table in accordance with the order specified by the row vector. The execution of the hierarchical window function may further include determining, for a first node in the hierarchy, a summary value corresponding to a first value of the first node and a second value of a second node descendent from the first node.

A system and method for implementing bloom filters in large scale applications is disclosed. The system and method include at least one processor configured to create a plurality of sharded bloom filters based on signatures stored in the memory, perform at least one lookup using the plurality of sharded bloom filters; and output a lookup result in real time.