Abstract: Methods and systems are provided for automatic classification of information in an adversarial machine learning setting. For example, a learner that includes multiple classifiers may perform data classification automatically. Each classifier may be trained with adversarial data of a different strength. For a given query to be classified, the learner is configured to intelligently select a classifier that is commensurate with the adversarial strength of the data inside the query, without explicit knowledge of that data or its adversarial strength.

Abstract: An initial Network on Chip (NoC) topology based on a set of initial requirements is incrementally modified to satisfy a set of different requirements. Each incremental modification includes minimizing a number of changes to existing components in the initial topology. Minimizing the changes includes preserving names of the existing components in the initial NoC topology.

Abstract: A resource host transmits a payload to a client device. The payload includes a first asset hosted by the resource host, and the first asset is associated with a first reference tag indicating a versioning status of the first asset. The resource host receives an Add Ref Instruction, wherein the Add Ref Instruction, which includes a custom reference tag indicating a user-selected versioning status of the first asset. The resource host associates a second reference tag with the first asset based on the custom reference tag.

Abstract: A system for allocation of one or more data structures used in a program across a number of processing units takes into account a memory access pattern of the data structure, and the amount of total memory available for duplication across the several processing units. Using these parameters duplication factors are determined for the one or more data structures such that the cost of remote communication is minimized when the data structures are duplicated according to the respective duplication factors while allowing parallel execution of the program.

Abstract: A computer measures for each column in many rows, a respective frequency of statements that filter the column in a workload of database statements, a respective count of distinct values used for filtration on the column in each statement individually, a respective frequency of each of the counts of distinct values used for filtration on the column across all of the database statements, and a respective value range of the column for each of many storage zones. A respective efficiency is measured for each of many distinct interleaved sorts. Each interleaved sort uses a respective distinct subset of the columns. Each interleaved sort is based on portions of each of the values for each row in a sampled subset of rows in each column of the subset of the columns of the interleaved sort. Efficiency measurement is based on frequencies of statements, value ranges of columns for each storage zone, and frequencies of counts of distinct values.

Abstract: A top K query directed at a table is received. The table is organized into multiple storage units. The top K query comprises a first clause to sort a result set in order and a second clause that specifies a limit on a number of results provided in response to the query. A table scan operator identifies a first set of rows from the table based on a scan set determined for the table and provides the first set of rows to a top K operator. The top K operator determines a current boundary based on the first set of rows and provides the current boundary to the table scan operator. The table scan operator prunes the scan set based on the current boundary and identifies a second set of rows from the table based on the pruning.

Abstract: An exemplary memory is configurable to operate in a low latency mode through use of a low latency register circuit to execute a read or write command, rather performing a memory array access to execute the read or write command. A control circuit determines whether an access command should be performed using the low latency mode of operation (e.g., first mode of operation) or a normal mode of operation (e.g., second mode of operation). In some examples, a processor unit directs the memory to execute an access command using the low latency mode of operation via one or more bits (e.g., a low latency enable bit) included in the command and address information.

Abstract: A transmission apparatus includes a transmission unit. The transmission unit transmits a packet including divided image data as payload data, the divided image data being obtained by dividing image data having a predetermined frame frequency into a predetermined number of frames, the image data having the predetermined frame frequency being subjected to mixing processing for each frame, image data of a previous frame and/or a subsequent frame being selectively used in the mixing processing, and further transmits metadata including information regarding the mixing processing in association with image data of each frame.

Abstract: A system, method, and computer-program product includes identifying a target hierarchical taxonomy that includes a plurality of distinct hierarchical taxonomy categories, extracting a plurality of distinct taxonomy tokens from the plurality of distinct hierarchical taxonomy categories, computing a taxonomy vector corpus based on the plurality of distinct taxonomy tokens, computing a plurality of distinct taxonomy clusters based on an input of the taxonomy vector corpus, constructing a hierarchical taxonomy classifier based on the plurality of distinct taxonomy clusters, converting a volume of unlabeled structured datasets to a plurality of distinct corpora of taxonomy-labeled structured datasets based on the hierarchical taxonomy classifier, and outputting at least one corpus of taxonomy-labeled structured datasets of the plurality of distinct corpora of taxonomy-labeled structured datasets based on an input of a data classification query.

Abstract: A method for classifying organizations involves obtaining, for an unknown organization, transactional data representing a multitude of transactions. The transactional data comprises a descriptive text for each of the multitude of transactions. The method further involves processing the descriptive text for each of the multitude of transactions to obtain one vector representing the unknown organization, categorizing the unknown organization using a classifier applied to the vector, and identifying a software service for the unknown organization, according to the categorization.

Abstract: An online content management service can collect and store receipts for a user from a variety of sources, including images captured by the user, messages received for the user at a messaging service or message management service, and/or receipts directly uploaded to the online content management service by a merchant. In the case of receipts provided as messages, a user can interact with a message management service to identify messages as receipts, and the message management service can upload such messages to the online content management service.

Abstract: Systems and methods for determining whether a user is part of a defined segment of all users makes use of a database of user information that includes rapidly searchable field values. Predetermined segment definitions can be evaluated using information from a user's record in the database to rapidly determine if the user is a member of the segment.

Abstract: A method of valuating a plurality of digital content items including: receiving the plurality of digital content items; for each received content item: establishing a plurality of attributes from content and characteristics of the content item; establishing a lifetime indicating a span of consumers interest in the content item; producing a valuation function for calculating a market value of the content item during its lifetime by finding and ranking nearest one or more previously processed content items having the plurality of attributes with closest similarity to the plurality of attributes of the received content item, performing weighted averaging of the valuation functions produced for the nearest one or more of the previously processed content items; and adapting, using “edge cutting” adaptation, the produced valuation function to a market response reflecting behavior of the consumers in response to the market values of the content item calculated by the valuation function.

Abstract: In one aspect, hierarchical image segmentation is applied to an image formed of a plurality of pixels, by classifying the pixels according to a hierarchical classification scheme, in which at least some of those pixels are classified by a parent level classifier in relation to a set of parent classes, each of which is associated with a subset of child classes, and each of those pixels is also classified by at least one child level classifier in relation to one of the subsets of child classes, wherein each of the parent classes corresponds to a category of visible structure, and each of the subset of child classes associated with it corresponds to a different type of visible structure within that category.

Abstract: A technique is described for generating a unified list (e.g., a list ribbon) of programs from a variety and disparate channels, the list for display on an over-the-top (OTT) client device. As an example, the unified list can be generated from OTT live channels and from over-the-air OTA and/or Advanced Television Systems Committee (ATSC) live channels. Further, the unified list can include OTT recordings on the cloud and OTA/ATSC recordings on the local hard drive connected to an OTA local DVR. Thus, the OTT device Client obtains the list from the DVR backend, instead of going to the local OTA client box for the local recordings.

Abstract: A recognition method includes retrieving an input including data of a first window size. The method further includes classifying the input based on comparison of warping distance of the input with a pruning threshold.

Abstract: Systems and methods for personalized visualization recommendation are described.

Abstract: Techniques are disclosed to provide correctness-preserving security for graph databases. In various embodiments, security context data associated with a user with respect to a graph database is stored. A query associated with the user with respect to the graph database is received. A path is allowed to be traversed in connection with responding to the query based at least in part on a grant of a traversal right, reflected in the security context data, to traverse one or more of a node and a relationship included in the path.

Abstract: Systems and methods for managing network devices include performing clustering operations for network devices based on attributes of the network devices. By comparing the results of subsequent clustering operations, changes in network device attributes can be readily identified and any network devices for which attributes have changed may be subject to further investigation or remedial action (e.g., blocking traffic to/from the network device). Clustering may also be used to conduct an inventory of network devices by identifying groups of network devices that have similar attributes.

Abstract: The present disclosure generally relates to methods of operating storage devices. The storage device comprises a controller comprising first random access memory (RAM1), second random access memory (RAM2), and a storage unit divided into a plurality of zones. The controller restricts the host to a maximum number of zones that can be in the open and active state at a time. Open zones can be switched to the closed state, and vice versa, upon a predetermined amount of time expiring. The maximum number of open zones is based on one or more amounts of time to: generate parity data, copy the parity data from the RAM2 to the RAM1, update the parity data, switch a zone from the open and active state to the closed state, and the amount of space in a temporary RAM1 buffer.

Abstract: A apparatus for credentialing users across multiple devices. The apparatus includes a processor connected to a network and at least a user device. Processor is configured to receive a credential data structure, verify the credential data structure, generate a credential block, and store the credential block in a data storage system. A plurality of user devices may access the network and the data storage system to view the verified credentials.

Abstract: Systems, methods, and devices for generating a transactional change tracking summary for a database. A method includes executing a transaction on a table of a database, wherein the table includes a micro-partition and the transaction is executed on the micro-partition. The method includes, in response to the transaction being fully executed, generating a change tracking entry comprising an indication of one or modifications made to the table by the transaction. The method includes storing the change tracking entry in a change tracking stream, wherein the change tracking stream includes one or more sequential change tracking entries that each correspond to a different transaction that is fully executed on the table.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed that improve detection of malware based on ecosystem specific data. An example apparatus includes a feedback weight controller to apply, with a machine learning model, a weight to feedback associated with a sample, the feedback obtained from at least a customer ecosystem and including endpoint feedback, human feedback, infrastructure feedback, and global feedback; and a sample conviction controller to, in response to a score based on the weighted feedback satisfying a threshold for a classification, indicate to a user, with the machine learning model, that the classification for the sample is malicious.

Abstract: Provided are techniques for mode-specific search query processing. A current search query is received from a user, wherein the user has a user profile. In response to determining that a query mode for the current search query is a guided mode, a query context of the current search query is determined. A classification for the current search query is determined. One or more search influencers are identified using the classification, where each of the one or more search influencers has a corresponding user profile. The current search query is rewritten based on the query context, a private portion of the user profile of the user, and a public portion of each corresponding user profile of each of the one or more search influencers. The rewritten search query is executed to generate search results, and the search results are returned.

Abstract: A computer-implemented method includes obtaining a plurality of textual records divided into clusters and a residual set of the textual records, where a machine learning (ML) clustering model has divided the plurality of textual records into the clusters based on a similarity metric. The method also includes receiving, from a client device, a particular textual record representing a query and determining, by way of the ML clustering model and based on the similarity metric, that the particular textual record does not fit into any of the clusters. The method additionally includes, in response to determining that the particular textual record does not fit into any of the clusters, adding the particular textual record to the residual set of the textual records. The method can additionally include identifying, by way of the ML clustering model, that the residual set of the textual records contains a further cluster.

Abstract: An example system includes a processor to receive a source code sample to be classified. The processor can execute a hybrid code analysis to generate an internal analysis state. The processor can extract features from the internal analysis state via a trained machine learning model modified using transfer learning. The processor can generate a label based on the extracted features via a machine learning classifier model trained on internal analysis states of hybrid code analyses.

Abstract: The invention provides a system for generating guest-specific service suggestions for a guest within a facility such as a hospitality facility. The system comprises a location device carried or worn by the guest within the facility; one or more location detecting devices arranged at the facility, the location detecting devices being arranged to detect the location device carried or worn by the guest, and to communicate one or more location detection signals to a computer implemented analytic module; wherein the analytic module is configured to determine location data for the location device carried or worn by the guest and, based on said location data and/or data from a person attribute database, predict a behavior of the guest from at least said location data and communicate behavior information to one or more service devices.

Abstract: Systems and methods for generating notifications based on extracted data from documents using a machine learning algorithm. The method includes receiving a document uploaded by a user including data corresponding to the user. The method further includes receiving an indication from the user granting permission to extract the data from the document. The method also includes extracting the data from the document using optical character recognition. The method further includes determining a document type based on the extracted data and document format data using a machine learning algorithm. The method also includes verifying the extracted data based on the determined document type and user data. The method also includes identifying a triggering event corresponding to the document based on the extracted data and the user data. The method further includes generating a notification corresponding to the triggering event.

Abstract: System and methods for relational time-series learning are provided. Unlike traditional time series forecasting techniques, which assume either complete time series independence or complete dependence, the disclosed system and method allow time series forecasting that can be performed on multivariate time series represented as vertices in graphs with arbitrary structures and predicting a future classification for data items represented by one of nodes in the graph. The system and methods also utilize non-relational, relational, temporal data for classification, and allow using fast and parallel classification techniques with linear speedups. The system and methods are well-suited for processing data in a streaming or online setting and naturally handle training data with skewed or unbalanced class labels.

Abstract: The present invention provides an image processing apparatus to execute a specifying step for specifying a change target for a common page contained in album data for a first subject containing the common page and an individual page for the first subject based at least on parameters related to the first subject, and specifying a change target for the common page contained in album data for a second subject containing the common page and an individual page for the second subject based at least on parameters related to the second subject.

Abstract: A system includes a relational database management system component and a column-oriented data processing component. The relational database system component stores database information in a row format. The column-oriented data processing component stores the database information in a column format. In response to a database update request, the relational database management system component updates the database information stored in the row format; the relational database management system component notifies the column-oriented data processing component of the database update request; and the column-oriented data processing component updates the database information stored in said column format. In response to a query request, the column-oriented data processing component generates a query response based on the database information stored in said column format. In this manner, the system is able to generate up-to-date reports without the need for extraction, translation and loading procedures.

Abstract: Embodiments presented herein provide apparatus and techniques for identifying and classifying processes and associated applications executing in a network. All processes executing in a network may be identified using a discovery process. The processes may be clustered based on associations between the processes. Suggested application entries may then be generated based at least in part on the clusters of processes. A configuration item type and a discovery pattern may be generated for each suggested application entry. A subsequent discovery process may use the configuration item type and discovery patterns to identify associated configuration items in the network.

Abstract: Cross-tabulation operation is performed within a columnar database management system. The columnar database management system receives a request to perform a cross-tabulation operation on a set of database tables. The columnar database management system determines values of cross-tabulation operation for each row of the result. The columnar database management system determines a domain for each value of the row dimension corresponding to a row combination. The columnar database management system determines an intersection set of the domains corresponding to values of the row dimensions for the row combination. The columnar database management system determines a value for the result column for the row combination as an aggregate value based on the records of the intersection set.

Abstract: Disclosed herein are system, method, and computer program product embodiments for providing an overall assessment of a combined inventory item and structure similarity to an initial inventory item and structure. A plurality of inventory items, stored in a database, maybe retrieved to generate a score value corresponding to each of the plurality of inventory items based on a plurality of facets describing the inventory item. Based on the generated score value, a subset of the plurality of inventory items may be determined based on data points representing the subset of the plurality of inventory items that are within a preconfigured Euclidean distance from a centroid representing a data point corresponding to the initial inventory item. One or more structures corresponding to the subset of the plurality of inventory items may be dynamically generated, and their combinations are scored for finding an alternate inventory item and structure.

Abstract: A system includes a memory configured to store instructions and at least one processor configured to execute the instructions. The instructions include accessing time series data, calculating statistical parameters of the time series data, identifying a set of external processing resources, and conveying the time series data and the statistical parameters to the set of external processing resources. The instructions include instructing the set of external processing resources to compute a similarity self-join of the time series data for a window size having a specified length. The instructions include obtaining sets of minimum subsequence distances from the set of external processing resources over a communications network. The full similarity self-join indicates, for each reference subsequence of the specified length within the time series data, a minimum value of distances between the reference subsequence and other subsequences of the specified length within the time series data.

Abstract: Systems and methods of the present disclosure facilitate managing information technology service level agreements. In some embodiments, the system includes a server that accesses a database storing a support ticket in memory. The support ticket can include a creation time and a service level agreement. The service level agreement can include a maximum response time. The server initiates, via the computer network, responsive to input from a computing device, a chat session associated with the computing device and the support ticket. The initiating can be associated with a time stamp. The server can be configured to determine a compliance with the service level agreement. The compliance can be computed as a difference between the time stamp and the creation time being less than the maximum response time. The server can be configured to generate a notification of the compliance with the service level agreement.

Abstract: Some examples herein describe time-series recognition and analysis techniques with computer vision. In one example, a system can access an image depicting data lines representing time series datasets. The system can execute a clustering process to assign pixels in the image to pixel clusters. The system can generate image masks based on attributes of the pixel clusters, and identify a respective set of line segments defining the respective data line associated with each image mask. The system can determine pixel sets associated with the time series datasets based on the respective set of line segments associated with each image mask, and provide one or more pixel sets as input for a computing operation that processes the pixel sets and returns a processing result. The system may then display the processing result on a display device or perform another task based on the processing result.

Abstract: A method, computer program product, and system includes a processor obtaining data including values and generating a value conversion dictionary by applying a parse tree based compression algorithm to the data, where the value conversion dictionary includes dictionary entries that represent the values. The processor obtains a distribution of the values and estimates a likelihood for each based on the distribution. The processor generates a code word to represent each value, a size of each code word is inversely proportional to the likelihood of the word. The processor assigns a rank to each code word, the rank for each represents the likelihood of the value represented by the code word; and based on the rank associated with each code word, the processor reorders each dictionary entry in the value conversion dictionary to associate each dictionary entry with an equivalent rank, the reordered value conversion dictionary comprises an architected dictionary.

Abstract: Techniques are provided for determining anomaly scores for transactions based on adaptive clustering of the location of a given user over multiple transactions.

Abstract: Systems and methods for providing relevant online content may include evaluating an action performed by a user identifier to determine the user's opinion regarding a topic. Content related to the topic may be selected and provided to an electronic device associated with the user identifier.

Abstract: A system for visualizing concepts within a collection of information analyzes a set of materials from at least one collection of information and defines an attribute space associated with the set of materials. The system then determines automatically similarity of members of the attribute space. The system then generates a graphical model of the members of the attribute space, where the generating includes generating a display of the members of the attribute space, each of the members having a respective display distance from other respective members of the attribute space reflective of the determined similarity.

Abstract: A location classifier generates location information based on textual strings in input text. The location information defines potential geographical relevance of the input text. In determining the location information, the location classifier may receive at least one geo-relevance profile associated with at least one string in the input text, obtain a combined geo-relevance profile for the document from the at least one geo-relevance profile, and determine geographical relevance of the input text based on the combined geo-relevance profile.

Abstract: Described is a technology for obtaining labeled sample data. Labeling guidelines are converted into binary yes/no questions regarding data samples. The questions and data samples are provided to judges who then answer the questions for each sample. The answers are input to a label assignment algorithm that associates a label with each sample based upon the answers. If the guidelines are modified and previous answers to the binary questions are maintained, at least some of the previous answers may be used in re-labeling the samples in view of the modification.

Abstract: For providing procedures, a synchronize module stores a plurality of procedures in a procedure database. Each procedure is indexed to a reference code. The synchronize module synchronizes the plurality of procedures to a mobile device. A retrieval module receives a first reference code at the mobile device and retrieves a first procedure indexed to the first reference code.

Abstract: A mechanism is provided in a data processing system for timeline-based social media data visualization. The mechanism receives social media data from at least one social media server. The mechanism filters the social media data to identify a plurality of social media posts related to a time-based event. The mechanism assigns the plurality of social media posts into a plurality of time periods within a timeline of the time-based event. The mechanism generates a timeline-based data visualization presenting the plurality of social media posts in relation to the timeline of the time-based event and presents the timeline-based data visualization.

Abstract: Diagnosing and detecting causes of an incident may comprise classifying the incident by keywords, searching for co-occurring and reoccurring group of incidents, summarizing commonalities in the group of incidents, correlating the group of incidents with causes, defining association rules between the commonalities, and predicting potential problems based on the correlated group of incidents with causes.

Abstract: Techniques for license reconciliation with multiple license types and restrictions includes grouping a collection of multiple software installation instances, a collection of multiple hardware devices and a collection of multiple software licenses into multiple clusters, generating a reconciliation matrix for each cluster, wherein each row in the reconciliation matrix represents a software installation instance or a hardware device, each column in the reconciliation matrix represents a license type and/or an individual license, and each cell in the reconciliation matrix represents a license requirement and applicability of each software installation instance or hardware device, solving each reconciliation matrix, and generating a license reconciliation plan based on the solved reconciliation matrices.

Abstract: Among other things, one or more techniques and/or systems are provided for maintaining a topic collection. That is, a topic collection (e.g., a vacation topic collection) may be created for a user, such that the user may store content associated with various applications (e.g., images from a social network app, vacation blogs, hotel price lists, sightseeing websites, etc.) as one or more entries within the topic collection. In this way, the user may easily organize, review, and/or share content through the topic collection. Recommendations of supplement content, which may be relevant to the topic collection, may be provided to the user. For example, entries within vacation topic collections of other users (e.g., to similar destinations) may be identified as supplemental content and recommended to the user. In this way, the user may accomplish a search task by organizing content into a single source.

Abstract: Techniques for license reconciliation with multiple license types and restrictions. A method includes grouping a collection of multiple software installation instances, a collection of multiple hardware devices and a collection of multiple software licenses into multiple clusters, generating a reconciliation matrix for each cluster, wherein each row in the reconciliation matrix represents a software installation instance or a hardware device, each column in the reconciliation matrix represents a license type and/or an individual license, and each cell in the reconciliation matrix represents a license requirement and applicability of each software installation instance or hardware device, solving each reconciliation matrix, and generating a license reconciliation plan based on the solved reconciliation matrices.

Abstract: Deterministic Finite Automatons (DFAs) and Nondeterministic Finite Automatons (NFAs) are two typical automatons used in the Network Intrusion Detection System (NIDS). Although they both perform regular expression matching, they have quite different performance and memory usage properties. DFAs provide fast and deterministic matching performance but suffer from the well-known state explosion problem. NFAs are compact, but their matching performance is unpredictable and with no worst case guarantee. A new automaton representation of regular expressions, called Tunable Finite Automaton (TFA), is described. TFAs resolve the DFAs' state explosion problem and the NFAs' unpredictable performance problem. Different from a DFA, which has only one active state, a TFA allows multiple concurrent active states. Thus, the total number of states required by the TFA to track the matching status is much smaller than that required by the DFA.