Abstract: A search and retrieval data processing system for retrieving classified data for execution against a cyber-security logic rules includes one or more hardware processors and memory, networked to communicably couple through a secure connection to a classified data database, the classified data database including an aggregated plurality of classified data records captured from a plurality of classified data sources; and the memory in communication with the processor, the memory storing an execution environment and the execution environment including an input port for receiving, from an entity, data associated with requested operations; a search engine for searching the classified data records of the classified database; and a logic execution module.

Abstract: Embodiments include systems and method for performing state driven bi-directional synchronization in a reflection database architecture. A set of changes to a series of data fields can be received at a first database, the set of changes being part of a first process flow. The first database can be a reflection of a second database over a partition. State driven synchronization can be performed by a bi-directional synchronization engine for at least a portion of the series of data fields between the first database and the second database. The bi-directional synchronization engine can be configured to bi-directionally synchronize data between the first database and the second database based at least in part on detecting a boundary state at one or more of the first database and the second database.

Abstract: An asset stored on a storage device of a computer system is detected to be omitted from an asset-specific access policy. Using a utilization history of the asset, a criticality of the asset is scored, generating a first criticality score for the asset. Using the first criticality score, the asset is classified into a policy category. A selected access policy selected from a set of access policies assigned to a set of assets in the policy category is applied to the asset, the selected access policy specifying an access restriction of the asset.

Abstract: A device searches for an anonymization of a data set using a heuristic search. The device receives a generalization lattice and one or more scoring functions. The device further can include selecting a start node in the generalization lattice. For each of the one or more scoring functions, the device can further include computing a path the generalization lattice from the start node that traverses the generalization lattice. In addition, the device can include determining an optimal path node from each of the one or more paths. Furthermore, the method can include selecting an optimal node from the one or more optimal path nodes.

Abstract: Methods, apparatus, and processor-readable storage media for block-level classification of unstructured data are provided herein. An example apparatus includes a host device comprising a processor coupled to memory, the host device being configured to communicate over a network with a storage system, and further being configured to: obtain a pointer to a page cache associated with an input-output operation for at least one page of unstructured data of a file; obtain an index node object of the file based at least in part on the pointer to the page cache; derive at least one characteristic of the file based at least in part on the obtained index node object; and provide an indication of the at least one characteristic to the storage system. The storage system determines whether to apply one or more functions to the unstructured data based on the indication.

Abstract: An automated interactive optimization method of short keyword queries for improving information retrieval from opaque (black box) search engines is disclosed. The method requires collecting data from several fact-checking websites, for creating dataset used for evaluation; estimating the relevance of posts/query results retrieved from a search engine to a given input document, by calculating the mean relevance error (MRE), based on estimating the minimal distance between words comprising both the retrieved posts and the input document; labeling a subset of claims for evaluation, by choosing a number of claims that gained the maximal and the minimal mean relevance error (MRE); and finding the most appropriate queries in order to retrieve the maximal number of relevant posts using an opaque search engine, by performing an interactive greedy search for the best word that should be added to the input query, for maximizing the corresponding posts retrieved by the search engine.

Abstract: Aspects of the present invention disclose a method, computer program product, and system for auto-scaling a query engine. The method includes one or more processors monitoring query traffic at the query engine. The method further includes one or more processors classifying queries by a plurality of service classes based on a level of complexity of a query. The method further includes one or more processors comparing query traffic for each service class with a concurrency threshold of a maximum number of queries of the service class allowed to be concurrently processed. The method further includes one or more processors instructing auto-scaling of a cluster of worker nodes to change a number of worker nodes available in the cluster based on the comparison, over a defined period of time, of the query traffic relative to a defined upscaling threshold and a defined downscaling threshold.

Abstract: In an aspect an apparatus for attribute data table matching is presented. An apparatus includes at least a processor. An apparatus includes a memory communicatively connected to at least a processor. A memory contains instructions configured at least a processor to receive an attribute data table from a user. A processor is configured to query an opportunity posting database as a function of a received attribute data table. A processor is configured to select an opportunity posting of an opportunity posting database as a function of at least an attribute data table criterion. A processor is configured to match an attribute data table to an opportunity posting as a function of at least an attribute data table criterion. A processor is configured to provide a match of an attribute data table to a user.

Abstract: In an aspect, an apparatus for attribute traversal 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 receive user data. At least a processor configured to identify a plurality of attributes of user data. At least a processor is configured to calculate a proficiency score. At least a processor is configured to generate a utility function. At least a processor is configured to determine an attribute enhancement datum. At least a processor is configured to present an attribute enhancement datum to a user.

Abstract: The present application discloses a method and apparatus for extracting the name of a POI, a device and a computer storage medium, and relates to the field of big data. An implementation includes: acquiring two or more text fragments identified from image data of the POI; constructing two or more candidate names using the text fragments; and ranking the candidate names using a pre-trained name ranking model, and determining the name of the POI according to the result of the ranking; wherein the name ranking model determines the probability of each candidate name as the name of the POI using at least one of a search web page feature, a document statistical feature and a semantic feature extracted from each candidate name, and ranks the candidate names according to the probabilities. With the present application, the name of the POI is automatically extracted with high accuracy. Compared with the manual review and annotation way in the prior art, a human cost is reduced.

Abstract: The disclosure relates to a method for providing a scraping-based service. The method for providing a scraping-based service includes: requesting and receiving at least one of scraping rule information defining a series of tasks for obtaining external data; collecting the external data by executing tasks according to the received rule information; and providing service information to a user using the collected external data. According to the disclosure, by providing a scraping service through a client terminal and a remote server in a distributed manner, it is possible to increase efficiency of a scraping task and actively cope with changes in a scraping target.

Abstract: Provided is a system and method for automated recommendation of new features for addition to an item based on user-generated feedback. In one example, the method may include receiving, via a user interface, a search query associated with an object, retrieving user-generated content that describes the object based on the received search query, identifying, via a machine learning model, one or more features to be added to the object based on the retrieved user-generated content, and outputting identifiers of the one or more features to be added to the object via the user interface.

Abstract: Processes and apparatuses for content personalization are provided, providing for rule configuration. Content personalization systems interpret user behavior and attributes along with the content users are interacting with, to build optimized predictive models of what content the user may want to see next. Those predictive models can be utilized to personalize content in one or more environments, including email, mobile and applications. Rules include filters applied to the predictive model output and/or the overall system output. Filters can be prioritized and iteratively applied or removed to adjust system output to satisfy desired result set criteria.

Abstract: The present disclosure is generally directed to methods, apparatus, and computer-readable media (transitory and non-transitory) for learning to automatically navigate interactive web documents and/or websites. More particularly, various approaches are presented for training various deep Q network (DQN) agents to perform various tasks associated with reinforcement learning, including hierarchical reinforcement learning, in challenging web navigation environments with sparse rewards and large state and action spaces. These agents include a web navigation agent that can use learned value function(s) to automatically navigate through interactive web documents, as well as a training agent, referred to herein as a “meta-trainer,” that can be trained to generate synthetic training examples. Some approaches described herein may be implemented when expert demonstrations are available. Other approaches described herein may be implemented when expert demonstrations are not available.

Abstract: Embodiments relate to a system and method to plan preparation of a meal that may include more than one dish. Online recipes are obtained from a database based on criteria set by the user. Recipes are analyzed for time and effort requirements at each step. If a meal includes more than one dish, a merge of the timelines is performed to determine if it is feasible to prepare all dishes concurrently. Suppliers that can supply all ingredients required by the recipes that meet all user criteria are recommended to the user.

Abstract: A data redistribution method, apparatus and a database cluster includes at least one first node, and an original table is stored on the at least one first node. A data redistribution process for redistributing the original table to the at least one first node and a second node is started, and the data redistribution process includes: starting a first transaction for creating a temporary table on the at least one first node and the second node, and associating an import operation for the original table with an import operation for the temporary table; starting a second transaction for selecting an old tuple from the original table based on a transaction identifier of the first transaction, and redistribute the selected old tuple to the temporary table. After the second transaction ends, metadata of the original table and metadata of the temporary table are exchanged.

Abstract: A workflow executed by an on-premise installation of the content management system can include a cloud workflow and an on-premise workflow relating to on-premise content retained in an on-premise repository managed by the on-premise installation of the content management system. A synchronization can be initiated between the on-premise content and a cloud copy of the on-premise content to reflect a change to either of the on-premise content or the cloud copy in the other of the on-premise content and the cloud copy. The cloud copy can exist at a location managed by a cloud-based installation of the content management system. Upon detection that the cloud workflow has been completed by the location using the cloud copy, a resumption of the on-premise workflow can be triggered using the synchronization between the on-premise content and the cloud copy of the on-premise content. Related systems, methods, products, etc. are described.

Abstract: A method involves receiving search queries, having search terms, submitted to at least one computerized search engine. For each query, a corresponding pairwise relation in the search queries is calculated. The corresponding pairwise relation is a corresponding probability of a potential edge relationship between at least two terms. Thus, potential edges are formed. A general graph of the terms is constructed by selecting edges from the potential edges. The general graph is nodes representing the terms used in the search queries. The general graph also is edges representing semantic relationships among the nodes. A hierarchical graph is constructed from the general graph by altering at least one of the edges among the nodes in the general graph to form the hierarchical graph.

Abstract: A data management services architecture includes architectural components that run in both a storage and compute domains. The architectural components redirect storage requests from the storage domain to the compute domain, manage resources allocated from the compute domain, ensure compliance with a policy that governs resource consumption, deploy program code for data management services, dispatch service requests to deployed services, and monitor deployed services. The architectural components also include a service map to locate program code for data management services, and service instance information for monitoring deployed services and dispatching requests to deployed services. Since deployed services can be stateless or stateful, the services architecture also includes state data for the stateful services, with supporting resources that can expand or contract based on policy and/or service demand. The architectural components also include containers for the deployed services.

Abstract: A system and method for automatic generation of a data tree structure are disclosed. A database stores contract metadata associated with a plurality of contracts. The metadata includes relationship information data regarding parentage and/or child relationship between a particular contract and other contracts among the plurality of contracts. A processor operatively connects to the database via a communication network and accesses the database via the communication network to retrieve the contract metadata including the relationship information data. The processor also implements a search engine; stores the retrieved contract metadata including the relationship information data onto the search engine for creating a linkage between data points; and automatically generates, based on the created linkage between the data points, both an application programming interface (API) and a data tree structure that displays inter-dependency between two or more sets of contracts among the plurality of contracts.