Abstract: Embodiments of the present invention are directed to facilitating data preprocessing for machine learning. In accordance with aspects of the present disclosure, a training set of data is accessed. A preprocessing query specifying a set of preprocessing parameter values that indicate a manner in which to preprocess the training set of data is received. Based on the preprocessing query, a preprocessing operation is performed to preprocess the training set of data in accordance with the set of preprocessing parameter values to obtain a set of preprocessed data. The set of preprocessed data can be provided for presentation as a preview. Based on an acceptance of the set of preprocessed data, the set of preprocessed data is used to train a machine learning model that can be subsequently used to predict data.

Abstract: Data is ingested from a source system. Ingesting the data includes determining corresponding chunk identifiers for a plurality of data chunks corresponding to the ingested data and for each of the plurality of data chunks, verifying whether the corresponding chunk identifier is included in a data structure tracking identifiers of data chunks that were already stored in a storage of a storage system before the data ingestion started and storing the data chunk in a storage based on the verification. After the ingesting is completed, deduplication of the ingested data chunks stored in the storage having a same chunk identifier is performed and the data structure is updated based on the deduplication.

Abstract: A method and apparatus are provided for avoiding target database constraint violations in a database replication system. The database replication system includes a source database and a target database, wherein target database transactions automatically abort due to constraint violations. Each database has one or more tables and at least one of the target database tables has one or more constraints. The database replication system replicates source database transactions. For each target database transaction corresponding to a replicated source database transaction, changes made at the source database are replicated to the target database. When it is detected that a replicated change causes a constraint violation as a result of one or more of the target database tables having one or more constraints, the applying of the database change to the target database of the database change is deferred and the database change is posted to an electronic list.

Abstract: A system includes hardware processors and a non-transitory memory storing instructions that, when executed by the hardware processors, causes the hardware processors to perform actions including receiving an input data set related to digital content, where the input data set includes a plurality of input entries. The actions also include matching one or more input words of each input entry of the plurality of input entries to one or more baseline words of one or more baseline entries of a baseline data set and generating an output data set including a plurality of output entries. Each respective input entry corresponds to a respective output entry of the plurality of output entries, and each respective output entry includes a baseline entry of the one or more baseline entries having a highest probability of matching the respective input entry and additional data associated with the respective input entry.

Abstract: Methods for enhancing compatibility of a document of an entity with an organization's database on a computer server. Methods may include using a computer hardware processor to digitize a document from a first format into a digital format, such as bytes, when the first format may not be compatible with the database. Methods may further include using a computer hardware processor to convert the document from a digital format into a second format, where the second format of the document may be compatible with the organization's database. Methods may include using a computer hardware processor to populate the database on the computer server with data from the document in the second format. Methods may further include storing the populated database and the document in the second format on the computer server.

Abstract: A system may include one or more tangible, non-transitory computer-readable media having stored thereon instructions, the instructions when executed to instruct one or more processors to: receive a platform-independent access binding data structure (a PIAB data structure), the PIAB data structure comprising a platform-independent representation of a subject class, a verb, an object, and a binding comprising a permission for the subject class to perform the verb on the object; convert the PIAB data structure to a first platform-specific binding for a first target platform; and cause the first platform-specific binding to be implemented on the first target platform.

Abstract: A system includes a controller, a database controlled by the controller, and a memory including an end-user executable code and a business software management code. The controller receives a user update to modify the end-user executable code, converts the user update to a machine language input, and, in response to the machine language input, modifies one or more of the end-user executable code, the database structure, and a documentation of the end-user executable code. In response to executing the program instructions associated with the modified end-user executable code on the end-user device, the controller generates a data collection GUI according to the modified end-user executable code and stores data in the database structure according to the modified end-user executable code.

Abstract: An information processing apparatus (100) according to the present disclosure includes an acquiring unit (132) that uses a trained encoder to acquire a feature value of each set of partial data forming first content; a calculating unit (133) that calculates a relative feature value that is a relative feature value between sets of partial data from the acquired feature values of the sets of partial data to calculate a relative feature value sequence indicating a feature of a structure of the first content; and a generating unit (134) that generates second content based on the relative feature value sequence of the first content and a feature value of optional data.

Abstract: In embodiments of field value search drill down, a search system exposes a search interface that displays one or more events returned as a search result set. A field-value pair can be emphasized in the field-value pairs of an event displayed in the search interface, and a menu is displayed with search options that are selectable to operate on the emphasized field-value pair of the event. The menu includes the search options to add search criteria of the emphasized field-value pair to a search command in a search bar of the search interface, exclude the search criteria of the emphasized field-value pair from a search, or create a new data search based on the emphasized field-value pair. A selection of one of the search options in the menu can be received, and the search command in the search bar is updated based on the search option that is selected.

Abstract: Providing an Artificial Intelligence (AI) and Internet of Things (IoT) based system and method that predicts the chronological requirements for various components of the file-being-stored, and then takes an appropriate storage action on each component based on the predicted chronological requirements.

Abstract: An embodiment of a system for determining the disposition of a hyperdocument and hyperdocument requests using a trained artificial neural network, including an information source, a requesting application, and a server containing a trained artificial neural network (ANN), the ANN being capable of evaluating the information, and providing results reflecting the evaluation to a requesting application is described.

Abstract: Systems and methods are described for modifying input and output (I/O) to an object storage service by implementing one or more owner-specified functions to I/O requests. A function can implement a data manipulation, such as filtering out sensitive data before reading or writing the data. The functions can be applied prior to implementing a request method (e.g., GET or PUT) specified within the I/O request, such that the data to which the method is applied may not match the object specified within the request. For example, a user may request to obtain (e.g., GET) a data set. The data set may be passed to a function that filters sensitive data to the data set, and the GET request method may then be applied to the output of the function. In this manner, owners of objects on an object storage service are provided with greater control of objects stored or retrieved from the service.

Abstract: An associative memory array includes a plurality of associative memory cells arranged in rows and columns where each first cell in a first row and in a first column has access to a content of a second cell in a second row in an adjacent column.

Abstract: A system can determine that a first destination inode number of a first destination inode of destination inodes is equal to a first source inode number of a file. The system can create a second file on the source file system, wherein the second file is stored in a second source inode of the source inodes having a second source inode number of the source inode numbers. The system can determine that the destination file system lacks an inode that has the second source inode number. The system can move a third file stored in the first destination inode to a second destination inode of the destination inodes that has a second destination inode number of the destination inode numbers. The system can migrate the first file to the destination file system, wherein the destination file system stores the first file with the first destination inode number.

Abstract: A storage system includes a storage device having a nonvolatile memory with a first and a second physical address and a host configured to insert a first journal logical address and a first target logical address into a journal mapping table. The storage device includes a flash mapping table storing the first journal logical address mapped to the first physical address, and the first target logical address mapped to the second physical address; a circuit configured to write the first journal data to an area of the nonvolatile memory to the first physical address corresponding to the first journal logical address according to the first mapping state, based on the journaling command; and to change the first mapping state of the flash mapping table to a second mapping state in which the first target logical address is remapped to the first physical address, based on the checkpointing command.

Abstract: Structured data comprising primary data is transformed into object-based data comprising the primary data and at least one search function. The object-based data when loaded into memory provides the search function as executable instructions for an object instance. When an application calls the object instance with search terms as input, the search terms are located within the primary data (which is loaded into memory) by the search function, and the object instance returns corresponding field values from the primary data associated with the search terms to the application.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, to detect system problems using social media. One of the method includes monitoring posts on a plurality of social network sites. The method includes identifying posts that include at least one of a plurality of keywords, at least some of the keywords indicative of system problems. The method includes tagging the identified posts. The method includes determining, based on the tagged posts, that a system problem is occurring. The method also includes raising an alert regarding the system problem.

Abstract: Certain embodiments described herein relate to data analysis systems, methods, and devices that comprise one or more processes and/or methodologies to add structure around a tabular database. By doing so, certain data analysis systems, methods, and devices can provide similar analytical functionalities as structured databases on one hand, as well as similar scalability and/or performance capabilities as tabular databases. In some embodiments, an add-in to a tabular data engine, such as Microsoft Excel, can be provided, through which a user can be allowed to input one or more dimensions and/or variables as desired for generating an analytical report. Based on such input, in certain embodiments, the system can be configured to build one or more data analysis expression (DAX) queries to dynamically generate a report, which can subsequently be displayed in the tabular data engine.

Abstract: Systems and methods for event data processing and provisioning using a multi-dimensional database platform including an Apache Kafka framework and an auxiliary database are provided. Methods may include receiving an event profile from a data producer module, tagging the event profile with a timestamp, a unique event identification code, an event type descriptor, a data producer identifier, and a workflow identifier. The method may also include logging, in the Apache Kafka framework, the timestamp and the event identification code, as part of a sequential stream of events; and storing, in the auxiliary database, the event identification code, the event type descriptor, the data producer identifier, and the workflow identifier.

Abstract: Systems and methods for query-based recommendation systems using machine learning-trained classifiers are provided. A service provider server receives, from a communication device through an application programming interface, a query in an interaction between the server provider server and the communication device. The service provider server generates a vector of first latent features from a set of first visible features associated with the query using a machine learning-trained classifier. The service provider server generates a likelihood scalar value indicating a likelihood of the query is answered by a candidate user in a set of users using a combination of the vector of first latent features and a vector of second latent features. The service provider server provides, to the communication device through the application programming interface, a recommendation message as a response to the query, where the recommendation message includes the likelihood scalar value and an indication of the candidate user.