Abstract: Technologies for unsupervised data classification include a computing device that generates a high dimensional profile for each column of a data store that is indicative of topological features of the column. The computing device also analyzes each column using multiple predetermined profiling rules and generates an initial classification for the columns based on profiling rule results. The initial classification may be applied to related columns based on clustering of the columns using the high dimensional profile. The computing device may train a machine learning model based on the initial classification and the high dimensional profile. Input features for training may include the profiling rule results and the high dimensional profile. Classifications may be provided to client devices via a predetermined interface. Other embodiments are described and claimed.

Abstract: A method, software, database, and system in which a query attribute is used as the basis for accessing stored attribute combinations and their frequencies of occurrence for individuals; and tabulating, based on frequencies of occurrence, those attribute combinations that are most likely to co-occur with the query attribute.

Abstract: The program directs a computer processor to implement a program that selects at least one substitute ingredient for a food recipe based on a plurality of determined criteria. The program receives a food recipe comprising one or more ingredients, instructions, and preparation time. The program determines time constraints of a user. The program identifies one or more Internet of Things (IoT) enabled cooking devices that are available in a kitchen associated with the user to carry out the instructions of the food recipe. The program searches a market database in a market to identify available options for the at least one substitute ingredient found in the market database based on a similarity level of the at least one substitute ingredient compared with at least one ambiguous ingredient in the food recipe, and selects the at least one substitute ingredient according to the plurality of determined criteria.

Abstract: Systems and processes disclosed herein perform an automatic remediation process. The automatic remediation process may be a log-based remediation process. Systems disclosed herein may obtain log files from an information management system and determine the occurrence of errors at the information management system based on error codes included in the logs. Further, the systems may access a knowledgebase to determine whether solutions for the errors have been previously generated. The solutions may include patches or hotfixes that can be applied to the information management system without removing user-access or stopping execution of the information management system. The systems may automatically update the information management system to address the errors. Alternatively, or in addition, the systems may alert a user, such as an administrator, of the existence of a solution to the error, and whether the solution may be applied without interrupting service or access to the information management system.

Abstract: A method for supporting files names in a storage system, the method may include receiving a first protocol request for creating an object having a requested object name that comprises one or more sets of slashes, wherein the first protocol does not use the one or more sets as hierarchy separators; wherein each set of slashes comprises one or more consecutive slashes; determining a role of each set of the one or more sets in a second protocol that uses slashes as hierarchy separators; and generating a path name for accessing the object, when using either one of the first and second protocols, wherein the generating is based on the requested object name and the role of each set.

Abstract: A data management system includes a first consistency zone, a second consistency zone, and a repository manager. The repository manager identifies a calculation event for a derived object of the second consistency zone, the derived object includes a cross-zone reference to the first consistency zone; and in response to identifying the calculation event: identifies an object in the first consistency zone associated with the cross-zone reference; sends a remote object request, to the first consistency zone, for the object with reference to an event of the first consistency zone specified by the cross-zone reference; obtains the object after sending the remote object request; and obtains a derived object instance based, at least in part, on a computation specification of the derived object and the object.

Abstract: Disclosed is a method for an intermediary mapping an de-identification comprising steps of retrieving datasets and meta data from a data source; selecting a target standard; mapping the retrieved datasets and the metadata to the target standard, wherein the datasets and the metadata are mapped to the target standard using one of, a schema mapping, a variable mapping, or a combination thereof; infer one or more of, variable classifications, variable connections, groupings, disclosure risk settings, and de-identification settings using the dataset mapping and metadata; perform a de-identification propagation using the mapped datasets, the mapped metadata, the inferred variable classifications, the inferred variable connections, the inferred groupings, the inferred disclosure risk settings, the inferred de-identification settings, or a combination thereof.

Abstract: According to one embodiment, an estimation device acquires a data set from history data. The history data includes a plurality of data IDs, path information, first and second qualitative variables. The data IDs respectively indicate a plurality of data flowing through a plurality of nodes. The path information indicates a path of the nodes for each of the data. The first and second qualitative variables are mutually-independent and indicate classifications of each of the data IDs. The data set includes a part of the data IDs having a first variable value assigned as the first qualitative variable. The estimation device estimates an overall relevance indicating a relevancy to the data set for each of the nodes. The estimation device generates a plurality of partial data sets. The estimation device estimates a partial relevance indicating a relevancy to each of the partial data sets for each of the nodes.

Abstract: Disclosed are systems and methods for improving interactions with and between computers in content providing, searching and/or hosting systems supported by or configured with devices, servers and/or platforms. The disclosed systems and methods provide a novel framework that provides an optimized ranking methodology for query suggestion and auto-completion tasks that messaging systems can implement and embed into their functionality. The disclosed framework can leverage the mail query logs on a personal level or on the aggregate (e.g., across all or a set of users on a network), and the mailbox content of each user to produce a comprehensive ranking function that generates ranked search suggestions for a mail search query for both person and company entities.

Abstract: This disclosure describes systems and methods that facilitate the generation of recommendations by traversing a graph. Walks that traverse the graph may be initiated from a plurality of different nodes in the node graph. In order to give greater or lesser weight to particular nodes, the walks may have different lengths depending on the nodes from which they are initiated, or an unequal amount of walks may be distributed between nodes from which walks are initiated. A plurality of walks through a node graph may be tracked, and visit counts or scores for nodes in the node graph may be determined. For example, scores may be increased for nodes that are visited by a walk initiated from a first node and a second walk initiated from a second node, or scores may be decreased for nodes that are not visited by a first walk initiated from a first node and a second walk initiated from a second node. Content corresponding to nodes may be recommended based on the scores or visit counts.

Abstract: A device may determine a price of a product based on first information concerning attributes of the product, and provide the price for display by a user device. The device may generate first hash values based on the first information, where a particular first hash value is associated with a particular attribute, and generate a first bit-string that includes the plurality of first hash values. The device may generate second hash values based on second information concerning the attributes of the product, where a particular second hash value is associated with the particular attribute. The device may generate a second bit-string that includes the second hash values, and determine a change to the particular attribute based on the first bit-string and the second bit-string. The device may determine a new price of the product based on the change, and provide the new price for display by the user device.

Abstract: Disclosed herein are systems and methods for classifying unstructured datasets according to a classification system and generating an enhanced, classified and structured data-set enabling efficient supplemental computer-based processing. The exemplary computer-implemented classification algorithms involve, for each entry in the input dataset, semantically interpreting a text-based occupation description, analyzing the description according to an ontology of interrelated “concepts” and identifying semantically relevant concept(s) and any associated descriptors specific to the classification system. The system is also configured to expand the list of relevant concepts to include concepts that bear a relationship thereto, scoring the various concepts and associated descriptors and identifying the concept(s) and descriptors that most accurately correspond to the input data.

Abstract: A system and a method are disclosed for receiving, from a source of a plurality of candidate sources, a payload comprising content and metadata. The system selects a destination to which to route the payload based on the source and the content, and generates an entry at the destination based on the content. The system inputs the metadata into a classification engine, and receives, as output from the classification engine, one or more classifications for the payload. The system applies a metadata tag to the entry, the metadata tag indicating the one or more classifications. The system receives a search request from a client device specifying at least one of the one or more classifications, and, in response to receiving the search request, provides the entry to the client device based on a matching classification.

Abstract: According to one implementation, a system includes a computing platform having processing hardware, a system memory storing a software code; and a machine learning model based classifier. The processing hardware is configured to execute the software code to receive tagging quality assurance (QA) data including multiple terms applied as tags and corrections to those tags, to identify, using the tagging QA data, a first problematic term, and to classify, using the machine learning model based classifier, the first problematic term as one of confusing or flawed. The processing hardware is further configured to execute the software code to obtain, when the first problematic term is classified as confusing, a comparative sample for clarifying use of the first problematic term, and to obtain, when the first problematic term is classified as flawed, modification data for editing a predetermined annotation taxonomy including the first problematic term.

Abstract: A method, software, database and system for attribute partner identification and social network based attribute analysis are presented in which attribute profiles associated with individuals can be compared and potential partners identified. Connections can be formed within social networks based on analysis of genetic and non-genetic data. Degrees of attribute separation (genetic and non-genetic) can be utilized to analyze relationships and to identify individuals who might benefit from being connected.

Abstract: A computer implemented method for classifying at least one source dataset of a computer system. The method may include providing a plurality of associated reference tables organized and associated in accordance with a reference storage model in the computer system. The method may also include calculating, by a data classifier application of the computer system, a first similarity score between the source dataset and a first reference table of the reference tables based on common attributes in the source dataset and a join of the first reference table with at least one further reference table of the reference tables having a relationship with the first reference table. The method may further include classifying, by the data classifier application, the source dataset by determining using at least the calculated first similarity score whether the source dataset is organized as the first reference table in accordance to the reference storage model.

Abstract: A client device operates by: extracting a set of deletion candidate data from application data stored in memory, wherein the deletion candidate data corresponds to a plurality of photographs; generating feature detection data for each of the plurality of photographs by performing a computer vision function on the each of the plurality of photographs; generating a subset of the set of deletion candidate data for deletion by selecting ones of the set of deletion candidate data that compare favorably to deletion criteria data, wherein the deletion criteria data indicates at least one unfavorable feature and wherein the subset of the set of deletion candidate data is generated by selecting ones of the plurality of photographs with feature detection data that indicates the at least one unfavorable feature is included in the ones of the plurality of photographs; and facilitating deletion of at least a portion of the subset of the set of deletion candidate data from the memory.

Abstract: A system and methods for generating and applying learning agents in simulated environments, in which an agent simulation is selected, one or more agent goals are received, and agents are created which are individual instances of the agent simulation with each agent having at least one of the agent goals, wherein the agents are used in the execution of an environment simulation which dynamically changes based on the collective behavior of the agents.

Abstract: The present disclosure relates to methods and systems for querying data in a data repository. According to a first aspect, this disclosure describes a method of querying a database, comprising: receiving, at a computing device, a plurality of keywords; determining, by the computer device, a plurality of datasets relating to the keywords; identifying, by the computer device, metadata for the plurality of datasets indicating a relationship between the datasets by examining an ontology associated with the datasets; providing, by the computer device, one or more suggested database queries in natural language form, the one or more suggested database queries constructed based on the plurality of keywords and the metadata; receiving, by the computing device, a selection of the one or more suggested database queries; and constructing, by the computer device, an object view for the plurality of datasets based on the selected query and the metadata.

Abstract: A method for assisting selection of an accommodation by an accommodation search system includes receiving user credentials from a user device; receiving trip parameters from the user device; determining a basic list of accommodations that correspond with the trip parameters; determining one or more factors that apply to each individual accommodation of the basic list of accommodations; applying a weight value to each of the one or more factors that apply to each individual accommodation of the basic list of accommodations; aggregating the weight values of the one or more factors that apply to each individual accommodation to determine an aggregate weighted score for each individual accommodation of the basic list of accommodations; sorting the basic list of accommodations into a sorted list of accommodations based on the aggregate weighted score for each individual accommodation; and providing the sorted list of accommodations to the user device for viewing by a user.