Abstract: Systems and methods of the present disclosure facilitate synchronizing data between a device management system and ticketing systems. In some embodiments, the system includes an update module, a mapping module, and a service board selection module. The update module may be configured to update ticketing information about a ticketing ticket on the ticketing system to match device management information about a device management ticket on the device management system. The mapping module may be configured to select a ticket category for a device management ticket on the device management system responsive to the device management information about the device management ticket. The service board selection module may be configured to select a service board for a ticketing ticket on the ticketing system.

Abstract: An internet data collection method includes steps of receiving a collecting instruction, the collecting instruction corresponds to target data that marked on a web page; retrieving a web address corresponding to the web page and the location information of the target data on the web page; and storing the web address and the location information as a tag to an operating end.

Abstract: An apparatus and method for academic search and analytics insights have been provided. The apparatus includes an ingestion component, obtaining data from external heterogeneous sources, to produce ingested data; a processing component for processing the ingested data; a search and analytics component for executing search queries on the ingested data and generating analytics insights on returned search result; and a storage component for storing the ingested data, the storage component acting as a communication data bus for the ingestion component, the processing component and the search and analytics component. Corresponding server and network system are have been provided.

Abstract: A method includes: determining presence or absence of duplication processing by a node 1000, the node constituting each of a plurality of distributed ledger systems and managing identification information of call processing from a program on another distributed ledger system 1; and executing the call processing after deduplication of the call processing is executed based on a specific policy.

Abstract: Apparatus and method are provided for tying together an URL request to a function in the database which returns media data. The invention provides for apparatus that receives a URL request for BLOB data from a web client and receives dynamic values specific to the web client from the web client. The URL is parsed to determine the function in a database and, if they exist, any parameters. A call is made to the function in the database specified in the URL and, if they exist, with parameters specified in the URL and with the dynamic values from the web client. The result can be streamed to the user.

Abstract: In an aspect, an apparatus for entity data aggregation is presented. An apparatus includes at least a processor and a memory communicatively connected to the at least a processor. A memory contains instructions configuring at least a processor to generate a web harvester. A web harvester is configured to extract entity data from an external database as a function of an extraction criterion. At least a processor is configured to classify extracted entity data to an entity data category. At least a processor is configured to aggregate extracted entity data into an entity profile as a function of an entity data category. At least a processor is configured to generate an entity search index as a function of aggregation of entity data.

Abstract: Transformation rule generation and validation functionality is provided herein. Transformation rules can be generated for one or more mappings in an alignment between a source database and a target database. The transformation rules can transform instance data from the source data model to a form matching the target data model. One or more transformation rules can be generated for a mapping between fields in a source database and a field in a target database. The transformation rules can be generated based on one or more source fields and a target field of a mapping, and one or more identified functions. Evaluating the transformation rules can include generating test data based on the transformation rules applied to instance data from the source database. The test data can be evaluated against instance data from the target database. The transformation rules and the evaluation results can be provided in a user interface.

Abstract: Systems and methods described herein facilitate the search and presentation of historical data for wireless network usage and provide a mechanism for high-redundancy, low-latency record retrieval of data from large data sets. Network devices divide data for a historical data store into separate record type groups, store metadata for each record type in an application database, partition each record type group by date in a historical record database that is different from the application database, and form, within each date partition, buckets of common hash values of a key parameter from each record. When a user performs a query, the network devices generate a record-specific query form based on the record type metadata to obtain lookup parameters; generate a search hash value using a key parameter from the lookup parameters; and generate a query expression based on the record type, lookup parameters, and the search hash value.

Abstract: Methods and systems are provided for generating training data for training a classifier to assign nodes of a taxonomy graph to items based on item descriptions. Each node has a label. For each item, the system identifies for that item one or more candidate paths within the taxonomy graph that are relevant to that item. The system identifies the candidate paths based on content of the item description of that item matching labels of nodes. A candidate path is a sequence of nodes starting a root node of the taxonomy graph. For each identified candidate path, the system labels the item description with the candidate path equivalently with leaf node or label of the leaf node. The labeled item descriptions compose the training data for training the classifier.

Abstract: Techniques are described for providing a ML data analytics application including guided ML workflows that facilitate the end-to-end training and use of various types of ML models, where such guided workflows may also be referred to as ML “experiments.” For example, the ML data analytics application may enable users to create experiments related to prediction of numeric fields (for example, using linear regression techniques), predicting categorical fields (for example, using logistic regression), detecting numerical outliers (for example, using various distribution statistics), detecting categorical outliers (for example, using probabilistic statistics), forecasting time series data, and clustering numeric events (for example, using k-means, density-based spatial clustering of applications with noise (DBSCAN), spectral clustering, or other techniques), among other possible uses of various types of ML models to analyze data.

Abstract: Systems, methods, and computer-readable media for determining at least one valid mood for a collection of media content items of a media library are provided.

Abstract: According to an aspect, a method for searching within user-generated reviews includes receiving, from a client device, a search query to search within a plurality of user-generated reviews relating to a plurality of entities, and identifying, in response to the search query, a set of user-generated reviews from the plurality of user-generated reviews that correspond to one or more search terms of the search query, where the set of user-generated reviews includes a user-generated review for a first entity and a user-generated review for a second entity. The first entity is different from the second entity. The method includes providing at least a portion of the user-generated review for the first entity and at least a portion of the user-generated review for the second entity for simultaneous display on a comparison layout of a user interface of the client device.

Abstract: An approach is provided in which a method, system, and program create a plurality of page clusters in feature space from a plurality of feature vectors corresponding to a plurality of unstructured pages. The method, system, and program product assign one of a plurality of machine learning models to each one of the plurality of page clusters based on a relationship in the feature space between the plurality of page clusters and a plurality of training clusters corresponding to the plurality of machine learning models. The method, system, and program product identify one of the plurality of page clusters that corresponds to a selected one of the plurality of unstructured pages, and transform the selected unstructured page into a structured page using a selected one of the plurality of machine learning models assigned to the identified page cluster.

Abstract: A data server may support segment identification based on a selected user profile. For example, a user may select a user profile as the basis for identifying a segment of additional user profiles. The server may identify attributes associated with the selected user identifier and generate an expression based on the identified subset. The expression may include a normalization function corresponding to at least one attribute. The normalization function may identify correlated attribute values for an attribute associated with the selected user profile. The data server may query a data storage system to identify the additional user profiles based on the expression. The data server may also support user defined Boolean expressions such that the expression is used to identify user identifiers associated with a first attribute and a second attribute.

Abstract: A method includes determining a change to storage parameters associated with storage of data objects in a storage network, where a data segment of the data objects is dispersed storage error encoded into a set of encoded data slices based on dispersed storage error encoding parameters, and where the set of encoded data slices is stored in the set of storage units. The method also includes determining a storage modification process for the set of encoded data slices based on the change to the storage parameters. The method also includes executing the storage modification process such that the set of encoded data slices are stored in the storage network in accordance with the changed storage parameters.

Abstract: A centralized document system identifies content items for presentation to a user based initially on a cold-start algorithm and subsequently based on machine-learned models. The system detects a first access by the user. The system generates a user attribute vector for the user and a content vector for each content item. The system selects a first content item based on the initial cold-start algorithm and modifies a user interface to include the first content item. The system identifies an interaction with the first content item by the user. The system detects a second access by the user. The system selects a machine-learned model based on a set of interactions by the user with displayed content items. The system applies the selected machine-learned model to the set of interactions and the user attribute vector to identify a second content item and modifies the user interface to include the second content item.

Abstract: A computer-implemented method for content-agnostic referencing of a binary data file, the method comprising: determining a length of the binary data file, the length comprising the number of bits of the binary data file; for the determined length, generating all permutations of data of the determined length; locating an index within the generated permutations, wherein the index is the starting position of the binary data file within the generated permutations; and using the length and the index to indicate the binary data file.

Abstract: Described herein are technologies that provide an element of security related to file system operations. Individual nodes in a file system, such as a directory or a file, can be associated with information that describes how to handle letter case when a file name included in a file system operation request is used to locate a file in the file system. For example, a case sensitive designation associated with a directory can require a case sensitive match between a file name included in a request and a file name included in the directory, in order to perform the requested file system operation. In another example, a case preferring designation associated with a directory first checks for a case sensitive match between file names. If a case sensitive match does not exist, then a case insensitive match between the file names can be used to perform the requested file system operation.

Abstract: An engine for resolving a query from a user to provide a dynamic actionable dashboard in a business operating system includes an MLET database, a data interface, a logic configured to process incoming queries, fetch data in relation to those queries, and render an actionable dashboard having data resulting from the queries. The MLET database comprises a plurality of templates (“MLETs”), each MLET being associated with a unique identifier and including a mechanism for accessing data relating to that identifier. The logic processes queries into constructs having a tokens and configurable inputs. If the query includes a unique identifier associated with an MLET in the MLET database, the MLET is used to fetch data responding to the query. If the query includes a unique identifier not associated with an MLET in the MLET database, the logic creates a new MLET using operational intelligence and stores it in the MLET database.

Abstract: Implementations described herein relate to methods, systems, and computer-readable media to write data records. In some implementations, a method may include calculating a data rate of a data stream that includes a plurality of data records and determining if the data rate of the data stream is less than an ingest threshold. The method may further include, if the data rate of the data stream is less than the ingest threshold, calculating a number of write requests per time unit based on the data stream; determining a storage capacity per storage bucket; determining a read interval for the data stream; based on the number of write requests per time unit, the storage capacity, and the read interval, selecting a size of time window per storage bucket; and writing the plurality of data records to a particular storage bucket.