Abstract: An information processing apparatus 4 includes: a transformation unit 423 configured to transform a plurality of tuples of feature vector data XV in a presentation space into a plurality of tuples of latent vector data ZV in a latent space; an extraction unit 423 configured to extract, based on the plurality of tuples of latent vector data, feature vector data having a shorter distance from query data DQ in the latent space than the other feature vector data, as neighbor data DNi from among the plurality of tuples of feature vector data; a generation unit 424 configured to generate, based on the neighbor data, a local model LM that outputs an estimation value dpi of a latent distance di when difference information Vi is inputted, the latent distance being a distance between the query data and the neighbor data in the latent space, the difference information being related to a difference, for each element of the features, between the query data and the neighbor data in the presentation space; and a calculation

Abstract: An autonomous data container and methods of use are disclosed. The autonomous data container includes a data storage structure for storing financial transaction information. The autonomous data container also includes an artificially intelligent agent stored as code within the container. The artificially intelligent agent can run on a system storing the autonomous data container. The artificially intelligent agent can access transaction information in the data storage structure and make predictions and/or decisions on a consumer's behalf. The artificially intelligent agent can make new purchases on the consumer's behalf. The artificially intelligent agent can also provide fraud alerts for the consumer.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for optimizing a digital resource search. One of the methods includes receiving a search query that specifies one or more parameters including a first parameter for a web resource request; determining that the first parameter is a particular parameter; in response to determining that the first parameter is a particular parameter: determining, using a historical search database, historical search data; predicting a subset of databases that are predicted to have web resources that are more likely responsive to the search query than second web resources; and obtaining a dataset that includes a plurality of web resources that each satisfy at least one parameter of the search query or at least partially satisfy the first parameter; and generating a plurality of search results for the web resource request.

Abstract: Methods, systems, and computer program products for identifying anomalous transformations using lineage data are provided herein. A computer-implemented method includes generating a set of column profiles for a corresponding set of columns within one or more datasets based at least in part on lineage data and glossary data, wherein the lineage data comprises information related to transformations performed on each column in the set by a computing platform, and wherein the glossary data comprises information related to one or more terms assigned to one or more of the columns; obtaining information related to a new transformation involving at least one column in the set of columns; comparing the new transformation to the set of column profiles to determine whether the new transformation is anomalous; and in response to determining the new transformation is anomalous, outputting an alert to a user of the computing platform.

Abstract: A chatbot server that provides an instant messaging service using a relay chatbot linked to multiple chatbots includes a receiving unit that receives, from a messenger server, a question message relevant to a service selected from multiple services and service account information corresponding to the selected service; a derivation unit that derives an answer to the question message using the relay chatbot corresponding to the service account information; and a transmission unit that transmits the answer to the messenger server, wherein the relay chatbot relays a user device to the multiple chatbots linked to the relay chatbot to derive the answer through at least one of the multiple chatbots.

Abstract: A determination device according to the present application has an acquisition unit and a determination unit. The acquisition unit acquires the search queries, which are the search queries input by a plurality of input customers who have input the reference query and input within a predetermined period. The determination unit determines whether a predetermined period is appropriate or not based on the attributes of the input customers who have input search queries or based on whether these search queries satisfy predetermined conditions or not.

Abstract: The disclosed embodiments related to multilateral portfolio compression using general large-scale linear optimization which pre-processes a model to decrease model size using domain knowledge to remove variables to reduce dimensionality, thereby making the model faster to solve and improving numerical characteristics. but it would not remove, for example, as much as half of the model, but rather a smaller fraction. The disclosed pre-processing enables an approximate solution for large, linear optimization models by automatically iteratively and selectively partitioning them into independently easily solvable sub-models. The sub-models are themselves linear optimization models, which can be solved with any preferred algorithm or library. The solutions for each sub-model are aggregated to obtain an acceptable, e.g., approximate, solution for a large model without solving the full model.

Abstract: A method for managing a file system includes obtaining, by a compression optimizing manager, a compression algorithm selection request for the file system, determining a set of selection inputs based on a set of file system parameters of the file system, applying a compression selection model to the set of selection inputs to obtain a compression algorithm selection, and initiating a file system compression implementation of the file system using the compression algorithm selection.

Abstract: A computer-implemented method for managing data quality is provided. The method comprising determining, by a rule engine, a number of critical data points in a number of different software modules. A classifier is identified based on a data type of the critical data points, and the classifier is bound to the critical data points. The classifier scans the critical data points for anomality to verify an ability to correctly process the critical data points. A data quality report is generated based on the scan and displayed to an end user in a graphical user interface.

Abstract: Data is gathered from a log file on a first application server, a log file on a second application server, a database on a database server, or any suitable combination thereof. By correlating the data from different sources, XP-Functions that execute in sequence on a single application server are identified and combined into a sequence referred to as an executable process chain (XP-Chain). The automatic process discovery server reconstructs end-to-end processes out of XP-Chains, even when the XP-Chains are executed on different application servers, based on log files and database data. A test script may be generated for an identified end-to-end process. By running the test script, proper functioning of the end-to-end process may be confirmed. Existing test scripts may be disabled for a formerly identified end-to-end process that is no longer found to be executed.

Abstract: Techniques are presented for generating semantic layers that are used to facilitate data analyses of subject datasets. The semantic layers are generated from data analysis configurations that characterize analysis environments pertaining to the subject datasets rather than from subject dataset metadata that is associated with the subject datasets. Data analysis attributes are extracted from configuration content objects that codify the data analysis configurations. A set of rules are accessed to facilitate mapping of the data analysis attributes to semantic model metadata that constitute the semantic layers. Some of the generated semantic layers comprise virtual data models. The virtual data models and/or recommendations associated with implementation of the semantic layers are presented to users. Certain portions of the semantic layers and/or the configuration content objects may be modified (e.g.

Abstract: Systems and methods for recommending content in a media system are described. In an embodiment, the method identifies a reference metadata tag associated with content in a database, retrieves a data structure storing information of learned associations between the reference metadata tag and a plurality of other metadata tags, the data structure defining a tree of nodes each associated with a corresponding metadata tag, a root node of the retrieved tree associated with the identified reference metadata tag. A path is extracted from the data structure, spanning from the reference metadata tag to a target metadata tag, the extracted path identifying a sequence of metadata tags defined by nodes along the extracted path. Recommended content items are returned based on the sequence of metadata tags identified by the extracted path.

Abstract: The disclosed embodiments related to multilateral portfolio compression using general large-scale linear optimization which pre-processes a model to decrease model size using domain knowledge to remove variables to reduce dimensionality, thereby making the model faster to solve and improving numerical characteristics. but it would not remove, for example, as much as half of the model, but rather a smaller fraction. The disclosed pre-processing enables an approximate solution for large, linear optimization models by automatically iteratively and selectively partitioning them into independently easily solvable sub-models. The sub-models are themselves linear optimization models, which can be solved with any preferred algorithm or library. The solutions for each sub-model are aggregated to obtain an acceptable, e.g., approximate, solution for a large model without solving the full model.

Abstract: Embodiments are directed to distributing records among storage partitions by maintaining a table of records. The table of records can be indexed based on an original partitioning key in the table of records. A plurality of counters can be initialized with each counter associated with a sub-range in a total range of key values for a secondary index partitioning key. Each record of the table of records can be read and a count of records in the associated sub-range can be accumulated in each counter. The number of records per partition can be determined based on the total number of records in the total range of key values and the number of available partitions and the records can be distributed to the available partitions in the storage system based on the number of records in each sub-range.

Abstract: Aspects of the disclosure relate to identifying entitlement rules based on a frequent pattern tree. A computing platform may retrieve entitlement data associated with a relational database, where the entitlement data is indicative of user entitlements to computing resources in an enterprise network. Then, the computing platform may generate, for the entitlement data, a frequent pattern tree. Then, the computing platform may compare a pair of branches and may detect a pattern associated with a pair of entitlements. Then, the computing platform may determine, based on the frequent pattern tree, a frequency of occurrence of the pattern. Then, the computing platform may identify, based on the frequency of occurrence, a rule associated with the pattern. Subsequently, the computing platform may trigger, via the computing device and based on the rule, an action related to one or more of the entitlements of the pair of entitlements.

Abstract: A data management device is provided, which includes an interpreting unit that interprets an input record, and convert the input record to abstract expression by which a correspondence relation between a data item and data itself is recognizable; and a converting unit that stores, in a storage unit, a data set, in which the data itself and index information capable of identifying the record are associated, as column data for each of the data items.

Abstract: The present disclosure provides a search method and device based on artificial intelligence and an electronic device. The search method based on artificial intelligence includes: obtaining a query; performing a word segmentation on the query to obtain a term sequence containing a plurality of terms; performing a structured analysis on the term sequence to generate a semantic pattern; performing a knowledge-based analysis on the term sequence based on the semantic pattern to generate a semantic analysis result; determining an understanding result corresponding to the query based on the semantic pattern and the semantic analysis result; and performing a search based on the understanding result corresponding to the query.

Abstract: A method, computer program product, and system for providing cross-lingual search results that retain cultural context include a processor(s) monitoring (with user permission) computing activities performed by the user, via a client. The processor(s) analyzes the computing activities to identify data comprising elements relevant to the user and relationships between the elements and the user. The processor(s) generates a data structure comprising the data. The processor(s) generates a search interface for obtaining entries in a first language to perform a query; the entries are search parameters embedded with a portion of the elements. The processor(s) obtains an entry in the first language. The processor(s) extracts the portion of the elements from the entry (cultural context for the entry). The processor(s) determines target languages for data responsive to the query. The processor(s) translates the search parameters and the cultural context into the target languages and executes searches on databases.