Abstract: Some embodiments provide a non-transitory machine-readable medium that stores a program. The program receives, from a client device, a request for information associated with a category. In response to the request, the program further accesses a storage to retrieve a first value associated with the category. The program also determines a set of values associated with the category based on a plurality of transactions. The program further determines an optimization level value associated with the category. The program also determines a second value associated with the category based on the first value, the set of values, and the optimization level value. The program further provides, by an application operating on the device, a graphical user interface (GUI) to the client device, the GUI comprising the second value.

Abstract: A method may include presenting a user interface on a computing device, the user interface including: a service provider input element identifying a service provider; a service identifier input element identifying a service; and a graph presentation area; executing a knowledge graph database query using a combination of the service provider and the service as input to a knowledge graph database; receiving tuple results in response to the executing, the tuple results including an allocation value property of the service provider attributable to the service provider with respect to the service; and generating in the graph presentation area, an interactive graph based on the tuple results including: representations of entities including the service provider and the service in the tuple results as nodes in the interactive graph, wherein a representation of the service provider includes the allocation value; and links connecting the representations of entities.

Abstract: Disclosed embodiments receive an event stream from a remote capture agent. The event stream includes timestamped event data generated by the remote capture agent based on network traffic monitored by the remote capture agent. A graphical user interface (GUI) is caused to be displayed for obtaining configuration information for configuring the generation of time-series event data from network packets captured by the remote capture agent. A set of statistics is generated from the time-series event data, and the configuration information is updated to trigger subsequent storage and processing of at least a portion of the event stream by one or more components on a network based on one or more of the statistics, a storage limit associated with the time-series event data, an index volume of the event stream, a historical trend associated with the statistics, or input through the GUI.

Abstract: In accordance with an embodiment, a data processing method includes: obtaining a first operation command, where the first operation command is used to perform data processing in a relational database; determining an acceleration policy of the first operation command, wherein the acceleration policy is used to accelerate a processing process of the first operation command; and performing an operation of the first operation command based on the acceleration policy.

Abstract: Data associated with a first set of managed flash storage devices of a cloud-based storage system is provided as an input to a machine learning model executed by a processing device that identifies one or more characteristics of the first set of managed flash storage devices from the data. A type of change associated with a second set of managed flash storage devices is determined by the machine learning model based on a comparison of the one or more characteristics of the first set of managed flash storage devices and one or more characteristics of the second set of managed flash storage devices. The type of change associated with the second set of managed flash storage devices is provided to a cloud services provider of the cloud-based storage system.

Abstract: A cloud-based personalization service utilizes a personalization model providing service users with tools to create, personalize, and manage their own user profiles, which are abstracted in the form of “personas,” that can learn from, and be shared across, different ecosystems of online services and applications. One or more personas may be locally instantiated on the user's various computing devices by a personalization system. The personalization service and system interoperate to enable users to set operating parameters, preferences, and content-filtering criteria for their personas. Users can strictly control the information and parameters that their personas expose to the services and applications to protect user privacy and enhance the quality of online interactions. The personalization model facilitates personalization of the user's personas to individual online services and applications based on context-awareness to further improve the relevance of delivered content and user experiences.

Abstract: A user can submit a visual query that includes one or more images with user free-form selected visual features of interest. Various processing techniques such as optical character recognition (OCR) techniques can be used to recognize text (e.g., in the image, surrounding image(s), etc.) and/or various object detection techniques (e.g., machine-learned object detection models, etc.) may be used to detect objects and particular visual features of objects (e.g., dress, sleeves, color, pattern, etc.) within or related to the visual query. Content related to the detected text or object(s) in combination with the user free-form selected visual feature of interest can be identified and potentially provided to a user as search results. As such, aspects of the present disclosure enable the visual search system to more intelligently process a visual query to provide improved search results and content feeds, including search results which are personalized to account for user search intent.

Abstract: A method includes determining an address associated with a data transform command in a container data structure which is in the data transform accelerator. The data transform accelerator is in communication with a host computing unit. In response to a determination that the address is in the container data structure, the method includes accessing the data transform command based on the address. The data transform command is in the host computing unit. The method includes obtaining metadata based on information in the data transform command. The metadata is in the data transform accelerator or spread out in the host computing unit memory and in the memory of data transform accelerator. The method includes configuring a data transform pipeline based on the metadata. The metadata can be shared in its entirety or partially by multiple data transform commands grouped together.

Abstract: Systems and methods for describing a composition of an article of manufacture are disclosed. In one aspect, a method includes receiving article composition data for an article of manufacture that identifies a set of parts of the article, a stated composition for each part of the set of parts, and a physical quantity of the stated composition. The method further includes classifying the stated composition of each part of the set of parts into a normalized composition that includes a set of normalized chemicals. The method further includes outputting an aggregated physical quantity of each normalized chemical for the set of parts of the article. The method can include classifying a normalized composition of each part into a material category within a hierarchical taxonomy based on the set of normalized chemicals of that normalized composition and outputting an aggregated physical quantity of each material category for the parts.

Abstract: In one embodiment, a system includes a processor configured to search a datastore to find records including a given field with a given value, the found records defining a dataset for consideration for archive having an aggregate data size, render to a display an indication of the aggregate data size of the dataset for consideration for archive, receive a user selection to archive at least part of the dataset, and purge the at least part of the dataset from the datastore and archive the at least part of the dataset into archive storage responsively to receiving the user selection, and a memory configured to store data used by the processor.

Abstract: A method for changing an itinerary based on a user change request is disclosed. The method may commence with receiving an itinerary request associated with one or more passengers. The method may continue with receiving a user itinerary change request associated with the itinerary network. The method may continue with generating an itinerary object associated with the user itinerary change request. The method may continue with modifying the itinerary network based on the itinerary object. The method may continue with processing the itinerary network using a topology of the itinerary network to create a plurality of tuples, the plurality of tuples including at least flight tuples and hotel tuples. The method may continue with performing a content search for the plurality of tuples for each of the one or more passengers. The method may continue with generating feasible itinerary solutions based on results of the content searches.

Abstract: Systems, and methods are described herein for integrated analysis of foreground and background communication data.

Abstract: The present technology provides for facilitating efficient identification of relevant metrics. In one embodiment, a set of candidate metrics for which to determine relevance to a user is identified. For each candidate metric, a set of distribution parameters is determined, including a first distribution parameter based on implicit positive feedback associated with the metric and usage data associated with the metric and a second distribution parameter based on the usage data associated with the metric. Such usage data can efficiently facilitate identifying relevance even with an absence of negative feedback. Using the set of distribution parameters, a corresponding distribution is generated. Each distribution can then be sampled to identify a relevance score for each candidate metric indicating an extent of relevance of the corresponding metric. Based on the relevance scores for each candidate metric, a candidate metric is designated as relevant to the user.

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: Various embodiments are generally directed to techniques for creating and utilizing multidimensional embedding spaces for data objects, such as to condition the data for input to a neural network, for instance. Some embodiments are particularly directed to detecting data types for structured data based on learned metadata. In many embodiments, an embedding space for a set of data objects may be customized with a set of dimensions that correspond to various characteristics of the set of data objects. For example, a set of data objects may correspond to a table with each data object corresponding to a data entry in the table. In such examples, correlations between different columns and/or within a column of data may be identified and utilized as metadata to improve classifications by the neural network.

Abstract: An AI-assisted document organization system includes an internet equipment, an identification equipment, a processing unit which is matched and connected to the internet equipment and the identification equipment. The processing unit includes a central processor, an artificial intelligence software and a document organization software. The document organization software includes document organization goals which include automatic document classification and identification, artificial intelligent data extraction, automatic data verification, automatic approval verification, compliance and regulatory compliance, document tracking and control, automatic reporting, and notification. The central processor drives the artificial intelligence software. The processing unit acquires document data through the identification equipment.

Abstract: A computer-implemented method, computer program product and computing system for maintaining a non-public content repository; and analyzing user-generated content to identify related content included within the non-public content repository.

Abstract: A method of storing data to a data storage and related device are provided, wherein data storage is divided into two or more variable size chunks, and each variable size chunks is divided into blocks, and the data storage comprises set of metadata. The data storage is also divided into two fixed size chunks. The method comprises: writing incoming write IO to a position of the corresponding size chunk in the data storage; setting the change indicator for the corresponding fixed size chunk to indicate that the corresponding fixed size chunk has been changed since it was divided into variable sized chunks. When change indicators indicate that division of the associated fixed size chunk or chunks into variable sized chunks should be changed, rechunking fixed size chunk into variable sized chunks is executed. Because of the change indicator, high deduplication is maintained even for offline deduplication in the data storage.

Abstract: A vehicle routing platform may store, in a first data structure, a value at a logical index for each pair of locations of a plurality of pairs of locations. The logical index, for a pair of locations, indicates whether a travel time has been determined. The vehicle routing platform may store, in a second data structure, an offset index for each predetermined logical index of one or more predetermined logical indexes of the first data structure. The offset index, for a predetermined logical index, may be based on a quantity of logical indexes preceding the predetermined logical index in the first data structure. The vehicle routing platform may store, in a third data structure, travel times between pairs of locations of a portion of the plurality of pairs of locations. The vehicle routing platform may determine a travel time, between a pair of locations, using the data structures.

Abstract: A system for modifying a website or interactive application, including a published database accessible via an end user data service to present the most up to date version of objects of the website, viewable and editable by at least one user, a draft database accessible via a designer data service and viewable and editable by at least one designer to store edits to the objects of the published database; a published database request handler to coordinate concurrent viewing and updating of the objects between the end user data service and the published database and a draft database request handler to coordinate concurrent viewing, editing and updating of the objects between the designer data service and the draft database and to merge edits and updates to the objects in both the published database and the draft database and to return the merged version of the objects without modifying the published database.