Abstract: Disclosed herein are an apparatus and method for positioning of uncollected points based on machine learning using matching wireless communication infrastructure points. The apparatus includes memory in which at least one program according to an embodiment is recorded and a processor for executing the program. The program may compare collected data acquired from wireless communication infrastructure with positioning data measured by a positioning target terminal and thereby extract matching feature points; create a fingerprint database of global grid cells, including uncollected points, for the extracted feature points in real time; and estimate the optimal composite location of the positioning target terminal based on the created fingerprint database.

Abstract: A method for managing data storage and retrieval and operated within a database management system includes retrieving a set of confidence data records from memory of the database management system, where a confidence data record of the set of confidence data records includes a set of data columns and one or more confidence columns populated with one or more data confidence values associated with data within one or more data columns of the set of data columns. The method further includes analyzing the set of confidence data records to produce a result, where the result includes a confidence level that is based on corresponding ones of the one or more data confidence values associated with the data within one or more data columns of the set of data columns.

Abstract: An approach for a non-factoid question answering framework across tasks and domains may be provided. The approach may include training a multi-task joint learning model in a general domain. The approach may also include initializing the multi-task joint learning model in a specific target domain. The approach may include tuning the joint learning model in the target domain. The approach may include determining which task of the multiple tasks is more difficult for the multi-task joint learning model to learn. The approach may also include dynamically adjusting the weights of the multi-task joint learning model, allowing the model to concentrate on learning the more difficult learning task.

Abstract: A system stores records of different entity types and processes search queries to determine search results comprising records that match the search query. The system receives a search query comprising search keywords from a source user. The system identifies a target user based on a search keyword received in the search query. The system determines a relationship between the source user and the target user. The system determines a relationship strength score for the relationship between the source user and the target user and ranks the search results based on the relationship strength score. The system provides the search results to the source user.

Abstract: An illustrative method includes a storage management system detecting an event within a storage system, determining, based on the event, an operation related to a compliance ruleset associated with a compliance policy, and providing a notification of the operation to an orchestration system configured to manage an execution of the operation by a computing system associated with the storage system.

Abstract: Data associated with storage media utilized by one or more storage systems is received. The data is provided as an input to a machine learning model executed by a processing device. The machine learning model identifies one or more deterministic characteristics from the data. The one or more deterministic characteristics associated with the storage media are received from the machine learning model. A data structure comprising the one or more deterministic characteristics is generated for use in a telemetry process to qualify types of storage media.

Abstract: In various embodiments, a method for generating from one or more keywords a list of related topics for organic search includes receiving, by a topic tool, an input of one or more keywords for which to generate a list of related topics. The method may further include acquiring, by a crawler, content from a plurality of different web content sources via one or more networks. The method may also include applying, by the topic tool, to the acquired content an ensemble of one or more key phrase extraction algorithms, one or more graph analyses algorithms and one or more natural language processing algorithms to identify a set of semantically relevant topics scored by relevance. The method may also include generating, by the topic tool, from the set of semantically relevant topics, a knowledge graph of related topics for the input of the one or more keywords.

Abstract: Systems, methods, and computer-readable media of which the method includes obtaining a knowledge graph comprising elements and relationships that connect together the elements, receiving a raw oilfield data, generating structured oilfield data based on the raw oilfield data, wherein the structured oilfield data represents information about the raw oilfield data, and generating unstructured oilfield data based on the raw oilfield data, the structured oilfield data, and the knowledge graph. The unstructured data includes data about the raw oilfield data, and one or more of the elements, one or more of the relationships, or both.

Abstract: Various methods, apparatuses/systems, and media for implementing a data quality check module for determining whether data is acceptable or not are disclosed. A processor collects all facts data corresponding to an agreement based on corresponding received distribution event data in accordance with margin requirements associated with the agreement and calculates statistical analysis data based on historical data points of the facts data for the agreement. The processor also creates and configures dynamic rules that are required to be applied for determining whether the agreement is in good order; verifies the statistical analysis data against the rules to determine anomaly data; marks the agreement as a good order agreement flag when it is determined that the anomaly data is within a predetermined threshold value; and automatically executes, in response to marking the agreement as a good order agreement flag, a straight through processing of the agreement.

Abstract: In one embodiment, a method includes receiving program content and data describing program content from a content source, and automatically identifying, based on user preferences of a first user, one or more relevant products or services displayed in the program content. Product-related metadata associated with the program content is identified. The product-related metadata including data relating to the one or more relevant products or services displayed in the program content. The program content is communicated to a display device for presentation to a first user in a first portion of the display device, and the product-related metadata is communicated to a second display device for presentation to a second user substantially simultaneously with the presentation of the program content in the first display device. A user commentary is received from the second device, the user commentary generated by the second user and associated with the program content or product-related metadata.

Abstract: The present disclosure discloses a data mining method, a data mining apparatus, an electronic device and a storage medium, relates to the technical field of the Internet, and in particular to the Internet big data processing technology. The method includes: acquiring a current article to be mined; obtaining information values required for each data identification strategy of multiple data identification strategies from the current article, and each data identification strategy is used for identifying a preset type of data; identifying a data type of the current article according to the information values required for each data identification strategy to obtain a data type identification result; and determining whether the current article belongs to any preset type of data according to the data type identification result.

Abstract: A system and method for providing recommendations based on current user interests. The method includes identifying at least one current variable, wherein each current variable is associated with a user device or a user; determining, based on the identified at least one current variable, at least one current user interest of a user profile, the user profile including at least one contextual insight, wherein each contextual insight is based on at least one signature for at least one multimedia content element associated with the user; searching for at least one multimedia content element that matches the at least one current user interest; and causing a display of the at least one matching content item as a recommendation.

Abstract: An indication of availability over time and resource usage is maintained for each computing device of a plurality of computing devices. An optimal combination of a subset of the plurality of computing devices is determined for each round of one or more rounds of training based on the availability over time and the resource usage for each computing device. A global model is generated utilizing the one or more optimal combinations of the plurality of computing devices and a query is performed utilizing the global model.

Abstract: A method for receiving an app-use contextual data set, applies artificial intelligence style machine logic to the app-use contextual data in order to generate a recommendation that the app should be subject to a recommended revision, in response to the generation of the recommended revision, makes the recommended revision in a dynamic manner, stores the app-use contextual data set in the form of a plurality of blockchain data structures, and operates around contextual reset/roll-back/restore scenarios in a hybrid cloud environment.

Abstract: A multi-layer elastic requisition stack may generate pool requisition tokens for controlling requisition of pooled database-compute resources. The elastic requisition stack may determine candidate databases for inclusion in elastic pools by analyzing historical utilization data and generating predicted utilization data. Based on the historical and predicted utilization data, the elastic requisition stack may determine multiplexing characteristics for the candidate databases and complement factors among the databases. The elastic requisition stack may compare unpooled database performance to pooled database performance to determine whether to pool the candidate databases.

Abstract: A system and method stores a database file into Flash memory or other write-constrained storage.

Abstract: A method for assessing validation points for a simulation model. The method includes: obtaining a reference measured value for at least two measuring points; determining a model form error for each of the at least two measuring points, based on a deviation between the reference measured value of the particular measuring point and a probability distribution for a simulation value at the measuring point, the probability distribution being obtained from the simulation model; forming a metamodel of the model form errors, based on the determined model form errors for the measuring points; determining an uncertainty of the metamodel for at least one further data point that is not contained in the measuring points; and defining the at least one data point as sufficient for a virtual validation if the uncertainty of the metamodel at the at least one further data point is less than a predefined limiting value.

Abstract: A method of labeling a dataset of input samples for a machine learning task includes selecting a plurality of pre-trained machine learning models that are related to a machine learning task. The method further includes processing a plurality of input data samples through each of the pre-trained models to generate a set of embeddings. The method further includes generating a plurality of clusterings from the set of embeddings. The method further includes analyzing, by a processing device, the plurality of clusterings to extract superclusters. The method further includes assigning pseudo-labels to the input samples based on analysis.

Abstract: The disclosed embodiments provide a system that facilitates the processing of network data. During operation, the system causes for display a graphical user interface (GUI) for configuring the generation of time-series event data from network packets captured by one or more remote capture agents. Next, the system causes for display, in the GUI, a first set of user-interface elements containing a set of statistics associated with one or more event streams that comprise the time-series event data. The system then causes for display, in the GUI, one or more graphs comprising one or more values from the set of statistics. Finally, the system causes for display, in the GUI, a value of a statistic from the set of statistics based on a position of a cursor over the one or more graphs.

Abstract: Described is a system and method for enabling visual search for information. With each selection of a search term, additional search terms are dynamically selected and presented to the user in conjunction with results matching the currently selected search terms. Likewise, a selected search term may be tokenized and a graphical token presented to the user to represent the selected search term.