Abstract: A method may include obtaining an application programming interface (API) document, such as an API user guide, API reference, or other API documentation, that includes information regarding an API resource, and extracting information from the API document, where the information including at least one function and at least one table that includes an attribute associated with the API resource. The method may also include extracting a description for each of the at least one functions from the API document, and comparing the extracted at least one table to a model of attributes to correlate extracted attributes with extracted functions. The method may additionally include compiling a machine-readable API specification for the API resource described in the API document based on the correlation between extracted attributes and the extracted functions.

Abstract: An architecture and processes enable computer learning and developing an understanding of arbitrary natural language text through collaboration with humans in the context of joint problem solving. The architecture ingests the text and then syntactically and semantically processes the text to infer an initial understanding of the text. The initial understanding is captured in a story model of semantic and frame structures. The story model is then tested through computer generated questions that are posed to humans through interactive dialog sessions. The knowledge gleaned from the humans is used to update the story model as well as the computing system's current world model of understanding. The process is repeated for multiple stories over time, enabling the computing system to grow in knowledge and thereby understand stories of increasingly higher reading comprehension levels.

Abstract: An architecture and processes enable computer learning and developing an understanding of arbitrary natural language text through collaboration with humans in the context of joint problem solving. The architecture ingests the text and then syntactically and semantically processes the text to infer an initial understanding of the text. The initial understanding is captured in a story model of semantic and frame structures. The story model is then tested through computer generated questions that are posed to humans through interactive dialog sessions. The knowledge gleaned from the humans is used to update the story model as well as the computing system's current world model of understanding. The process is repeated for multiple stories over time, enabling the computing system to grow in knowledge and thereby understand stories of increasingly higher reading comprehension levels.

Abstract: In order for the feature extractors to operate with sufficient accuracy, a high degree of training is required. In this situation, a neural network implementing the feature extractor may be trained by providing it with images having known correspondence. A 3D model of a city may be utilized in order to train a neural network for location detection. 3D models are sophisticated and allow manipulation of viewer perspective and ambient features such as day/night sky variations, weather variations, and occlusion placement. Various manipulations may be executed in order to generate vast numbers of image pairs having known correspondence despite having variations. These image pairs with known correspondence may be utilized to train the neural network to be able to generate feature maps from query images and identify correspondence between query image feature maps and reference feature maps. This training can be accomplished without requiring the capture of real images with known correspondence.

Abstract: A method of classifying an electronic document from an electronic media source includes generating statistical data from one or more training documents and creating a plurality of classification rules, including creating at least one topic model-based classification rule using the statistical data and creating at least one query-based classification rule using one or more user defined categories and the statistical data. The method further includes classifying the electronic document using the at least one topic model-based classification rule. Example systems for classifying an electronic document from an electronic media source are also disclosed.

Abstract: Methods, systems, and computer-readable media for implementing rule-based triggering in a provider network are disclosed. When conditions are met for one or more triggers, one or more rules that comprise the one or more triggers are determined. The conditions are determined in a provider network comprising a plurality of resources. One or more actions are determined in the one or more rules that comprise the one or more triggers. The one or more actions are performed, comprising modifying one or more of the resources in the provider network.

Abstract: Specifying rules for processing data included in fields of elements of a dataset includes rendering user interface elements associated with a respective condition. The user interface elements include: first subsets of user interface elements, at least some of which are associated with an input value derived from at least one field, and second subsets of user interface elements, each configured to receive user input associated with a respective condition. Conditions are applied to at least a first element of the dataset based on user input received from at least some of the user interface elements, in response to receiving user input for a first user interface element associated with a first field. Instructions are generated for applying one or more selected conditions associated with fewer than all of the user interface elements, the selected conditions including at least a condition associated with the first user interface element.

Abstract: Aspects of the invention include receiving, using a processing system, an actual user location trajectory that includes a plurality of geographic locations of places visited by a user. It is determined that at least one of the plurality of places visited by the user has been identified as a sensitive place. An obfuscated user location trajectory is created that preserves the privacy of the sensitive places that is consistent with the actual user location trajectory that conforms to a valid street route on a map, preserves spatiotemporal correlation between geographic locations, and is consistent with geographic locations visited by the user in the past. Contents of the obfuscated user location trajectory are output to an application in place of contents of the actual user location trajectory.

Abstract: Embodiments of the disclosure are directed to methods and systems for selecting targets for an advertisement campaign. A method may comprise adjusting one or more slider axes that control selection methods, wherein the selection methods may comprise using target demographic data, target behavioral data, filtering criteria, and/or ranking criteria. Then, an analysis application may complete analysis using the input adjustments to determine a selection of potential targets. The analysis application may be operable to complete multiple methods of analysis (or selection), wherein the user may have input and/or control over the use of the methods.

Abstract: An extraction apparatus includes an input-data analysis unit that, when an extraction process is performed on input data containing a plurality of XBRL files using a combination of a plurality of extraction criteria, each of the extraction criteria directly specifying an element and an aspect of each of the plurality of XBRL files, calculates, from the input data, distribution information containing distribution of values of individual aspects of a plurality of elements that are individually provided by the plurality of XBRL files, and an application-sequence determining unit that determines an application sequence of the plurality of extraction criteria by referring to the calculated distribution information. Hence, the extraction apparatus can extract XBRL data pieces containing data items to be validated against a validation rule from the input data rapidly.

Abstract: A method implemented by at least one server computer is provided, including: providing, over the Internet, access to a plurality of topics, wherein each topic includes, and further provides access to, a plurality of posted items; recording interaction data for the plurality of topics, the interaction data identifying user activity occurring within each of the topics; analyzing the interaction data to identify clusters of topics that exhibit similar behavioral patterns; for each cluster of topics, generating a community that includes the topics in the cluster; providing, over the Internet, access to the communities, wherein accessing a given community further provides access to the topics included in that community, which further provide access to the posted items that are included in the topics within that community.

Abstract: An engine architecture for processing finite automata includes a hyper non-deterministic automata (HNA) processor specialized for non-deterministic finite automata (NFA) processing. The HNA processor includes a plurality of super-clusters and an HNA scheduler. Each super-cluster includes a plurality of clusters. Each cluster of the plurality of clusters includes a plurality of HNA processing units (HPUs). A corresponding plurality of HPUs of a corresponding plurality of clusters of at least one selected super-cluster is available as a resource pool of HPUs to the HNA scheduler for assignment of at least one HNA instruction to enable acceleration of a match of at least one regular expression pattern in an input stream received from a network.

Abstract: According to an embodiment of the present invention, methods, systems, and computer readable media are provided for collecting statistics for use in optimizing a database query. Collected statistics for the database are compared to corresponding predetermined states of conditions for optimizing the database query. One or more collected statistics in compliance with the corresponding predetermined states of conditions are identified based on the comparison. Collection of the one or more identified statistics for the query optimization is disabled.

Abstract: Exemplary methods, apparatuses, and systems receive, from a first user device associated with a first user, location data representing a current physical location of the first user. A request for the current physical location of the first user is received from a second user device associated with the second user. In response to the received selection, the current physical location of the first user based upon the shared location data is transmitted to the second user device. A selection of a third party service is received from the second user device. The current physical location of the first user is transmitted to a server associated with the third party service within a request for the third party service to send the a service or product to the current physical location of the first user.

Abstract: Methods and systems may provide for technology to extract relationship data from one or more social networks and generate a trust network based on the relationship data, wherein the trust network identifies one or more trusted individuals. The technology also grants access to the smart device system with respect to the one or more trusted individuals.

Abstract: A system for generating at least one policy includes a static permission database containing a plurality of static permission records identifying access permissions for at least one credential holder to at least one resource, a policy database, and a processor to analyze the plurality of static permission records to generate the at least one policy, wherein an outcome of execution of the at least one policy corresponds to the plurality of static permission records.

Abstract: A method for processing a time series includes dividing, with a processing device, the time series into a plurality of windows by time; extracting at least one group of similar subsequences from a current window among the plurality of windows; and updating a candidate list on the basis of comparison between similar subsequences in each group of the at least one group with k characteristic subsequences in the candidate list; wherein the k characteristic subsequences are k characteristic subsequences with a greatest number of occurrences in at least processed parts of the time series.

Abstract: There is provided a method for generating features for use in an automated machine learning process, comprising: receiving a first training dataset comprising unclassified raw data instances each including a set of objects of arbitrary types; applying a function to each data instance to calculate a set of first results; generating a set of classification features each including the function for application to a newly received data instance to calculate a second result, and a condition defined by a respective member of the set of first results applied to the second result; applying each classification feature to each instance of an unclassified second training dataset to generate a set of extracted features; selecting a subset of pivotal classification features from the set of classification features according to a correlation requirement between classification variable(s) and each respective member of the set of extracted features; and documenting the subset of pivotal features.

Abstract: Electronically received data is validated based on a digital data image that is scanned from a paper document. Known paper document source entities, paper document types and associated paper document configuration information are stored in a database. The paper documents are converted to digital data images and optically processed to identify respective source entity and document type information represented within the digital data images. Appropriate document configuration information is retrieved based on association with the detected type of document. Validation target data is extracted from the digital data images based on the configuration information and processed. The electronically received data is validated based on the extracted and processed validation target data.

Abstract: Methods and systems for a quantum computing approach to solving challenging, e.g., NP-complete, problems in transportation. One of the methods includes (a) ingesting transportation-related data into a graph structure, the transportation-related data being associated with a transportation system; (b) identifying a transportation metric associated with the transportation system; (c) identifying at least one attribute associated with the transportation-related data, where the transportation metric is based at least in part on the attribute; (d) using a quantum computer to derive an operational parameter for the attribute that improves the transportation metric; and (e) applying the operational parameter to the operation of the transportation system.

Abstract: A sensor system may comprise a sensor; a processor in electronic communication with the sensor; and/or a tangible, non-transitory memory configured to communicate with the processor, the tangible, non-transitory memory having instructions stored thereon that, in response to execution by the processor, cause the processor to perform operations. The operations may comprise recording, by the sensor, a preliminary type data sample; and/or applying, by the processor, a mapping function having a plurality of tuned parameters to the preliminary type data sample, producing a desired type data output.

Abstract: A sensor system may comprise a sensor; a processor in electronic communication with the sensor; and/or a tangible, non-transitory memory configured to communicate with the processor, the tangible, non-transitory memory having instructions stored thereon that, in response to execution by the processor, cause the processor to perform operations. The operations may comprise recording, by the sensor, a low quality data sample; and/or applying, by the processor, a mapping function having a plurality of tuned parameters to the low quality data sample, producing a high quality data output.

Abstract: Methods, systems, and computer program products for detecting losses in electrical networks are provided herein. A computer-implemented method includes computing a consumption estimation for each consumer associated with a network; determining a difference between (i) the consumption estimation and (ii) actual consumption for each consumer; clustering the consumers into a cluster based on a consumption pattern associated with each consumer; determining a level of deviation of (i) the consumption pattern associated with each consumer from (ii) a consumption pattern representative of the cluster; clustering the consumers into two or more clusters based on a consumption pattern during a first interval of time and during a second interval of time; determining, for each consumer, a level of evolution from (i) a first cluster during the first interval to (ii) a second cluster during the second interval; and identifying consumers associated with a given loss within the network.

Abstract: A method for processing a time series includes dividing, with a processing device, the time series into a plurality of windows by time; extracting at least one group of similar subsequences from a current window among the plurality of windows; and updating a candidate list on the basis of comparison between similar subsequences in each group of the at least one group with k characteristic subsequences in the candidate list; wherein the k characteristic subsequences are k characteristic subsequences with a greatest number of occurrences in at least processed parts of the time series.

Abstract: The method for model management includes, within a testing platform: building candidate model(s), validating the candidate model(s), and selectively deploying the candidate model(s) into a production environment. The method can optionally include, within a production environment: detecting a class instance based on the raw data using deployed model(s) within the production environment, and transmitting a notification to an endpoint associated with the detected class.

Abstract: To provide an arrangement of virtual machines on physical machines, at least one controller compares indicators associated with plural different layouts of the virtual machines on the physical machines, wherein the indicators provide information regarding performances of corresponding layouts. The at least one controller selects one of the plural layouts based on the comparing.

Abstract: The Support Vector Machine (SVM) has been used in a wide variety of classification problems. The original SVM uses the hinge loss function, which is nondifferentiable and makes the problem difficult to solve in particular for regularized SVMs, such as with l1-norm. The Huberized SVM (HSVM) is considered, which uses a differentiable approximation of the hinge loss function. The Proximal Gradient (PG) method is used to solving binary-class HSVM (BHSVM) and then generalized to multi-class HSVM (MHSVM). Under strong convexity assumptions, the algorithm converges linearly. A finite convergence result about the support of the solution is given, based on which the algorithm is further accelerated by a two-stage method.

Abstract: An apparatus includes a network interface. The apparatus includes a processor coupled to the network interface. The apparatus further includes memory accessible to the processor. The memory includes instructions executable by the processor to perform operations. The operations include receiving user history data based on operation of a customer premise equipment device. The operations include determining additional information based on information extrapolated from the user history data. The operations include dynamically generating a user interface based on the user history data and based on the additional information. The operations further include initiating a transmission of the user interface to the customer premise equipment device.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for data aggregation.

Abstract: A method and system for determining the likelihood or similarity ratio that a selected media file of interest is related to one or more predetermined media files is provided that utilizes, combines, analyzes, and evaluates different categories of data and metadata extracted from each media file to generate a media file identifier for each media file that can then be used as a basis to compare any two media files to each other.

Abstract: Exemplary methods, apparatuses, and systems parse data with a plurality of pattern matching rules. Pattern matching rules are applied in an ordered sequence and a first rule is applied to the data before a second rule is applied to the data. In response to determining the second rule matches the data, the sequence is reordered to apply the second rule prior to the first rule.

Abstract: Technology for improving evaluation of policies comprising multiple rules is disclosed. By generating a policy evaluation tree controlling, for any given policy state, which rules should be evaluated next, policy optimization can be performed off-line prior to policy evaluation. For a policy, a policy evaluation tree can be generated such that each node in the tree corresponds to a policy state and each child node corresponds to a policy state that may result from an action that may be taken from its parent policy state. Policy evaluation trees may be generated by iteratively generating, from an initial policy state, possible next states as child states until a result of the policy is determined. Some next possible policy states may be pruned from the tree based on conditions such as having a high cost of evaluation compared to the likelihood a rule will yield an interesting result.

Abstract: An event-notification system provides for monitoring resource-status parameters so as to repeatedly generate resource-status values for each of N resource-status parameters applicable to the resources. Each datapoint specifies a resource, a time of collection, and the values of parameters for the resource at the time. The datapoints are represented in an N-dimensional space, including N dimensions corresponding to the resource-status parameters and one dimension devoted to time. The datapoints are clustered on a proximity basis. The clusters are manually classified as Normal or Ack-Abnormal. A machine-learning engine develops a model that allows the classifications to be automated. Alerts are sent for respective Abnormal clusters rather than for each abnormal datapoint, thus reducing the amount of data an administrator must deal with to address potential problems.

Abstract: A system coupled to a packet-based network is configured to predict the locations of mobile devices that have communicated with the packet-based network. The system includes a request processor configured to detect location events associated with mobile devices communicating with the packet-based network, each location event corresponding to a time stamp and identifying a geo-place in a geo database. The geo-places include geo-blocks and geo-fences. The system further comprises a location prediction subsystem configured to construct first feature space using first location events and second feature space using second location events, and to extract a set of labels from third location events. The location prediction subsystem is further configured to train a prediction model using the first feature space and the set of labels, and to apply the prediction model to the second feature space to obtain prediction results.

Abstract: A computing device configured to determine an optimal value for a control of a drilling operation is provided. An event stream processing engine (ESPE) instantiated. The ESPE is instantiated to execute an objective function model determined using historical drilling data. The objective function model maximizes a rate of penetration for a previous drilling operation. The historical drilling data includes a plurality of values measured for each of a plurality of drilling control variables during the previous drilling operation. Measured drilling data that includes current drilling data values for a current drilling operation is received by the ESPE. The received, measured drilling data is processed through the ESPE instantiated to execute the objective function model to determine an optimal value for a control of the current drilling operation. The determined optimal value is output by the ESPE for the control of the current drilling operation.

Abstract: Embodiments of the present invention disclose a method, computer program product, and system for updating database statistics using profiles. A computer determines whether an application credential has authority to update a database statistic of a target database, based, at least in part, on a profile. Responsive to determining that the application credential has authority to update the database statistic, the computer loads the transformed data into the target database. The computer determines whether an update to the statistic is to be performed. Responsive to a determination that the update to the statistic is to be performed, the computer generates a profile name. The computer determines whether the generated profile name exists within a system catalog of the target database. Responsive to a determination that the generated profile name exists, the computer transmits a command to update the database statistic of the target database using the generated profile name.

Abstract: An advanced intelligence engine (AIE) for use in identifying what may be complex events or developments on one or more data platforms or networks from various types of structured or normalized data generated by one or more disparate data sources. The AIE may conduct one or more types of quantitative, correlative, behavioral and corroborative analyses to detect events from what may otherwise be considered unimportant or non-relevant information spanning one or more time periods. Events generated by the AIE may be passed to an event manager to determine whether further action is required such as reporting, remediation, and the like.

Abstract: A storage space management method and apparatus, where the method and apparatus are applied to a non-volatile memory (NVM). In a feature set that includes M image features of M idle blocks in storage space of the NVM, an idle block whose image feature is highly similar to an image feature of data to be written into the NVM is determined such that the data is written into the idle block. In this way, wear and energy consumption problems are considered during storage space allocation, and a write operation of an idle block in storage space of an NVM can consume less energy, thereby extending a life span of the NVM and reducing write operation energy consumption.

Abstract: Described is system and method for cognitive recognition. The system receives a multi-dimensional scene array as input data. A foveation module divides the multi-dimensional scene array into a plurality of sub-arrays and outputs contents of a currently selected sub-array. The contents are clustered with a hierarchical clustering module to generate a spatially invariant hierarchical cluster of the contents comprising a plurality of components which are based on a statistical distribution of co-occurrence of features across the currently selected sub-array. Task-relevant components are selectively gated and robustly maintained into a component memory location of a pattern bank with a working memory module with an input gating module. If the task-relevant components activate an abstract category module based on pattern matching, then a category recognition label is generated for the contents of the currently selected sub-array with an executive control module.

Abstract: A computer-implemented method, system, and computer program product for producing a semantic query by example are provided. The method includes receiving examples of potential results from querying a database table with an associated ontology, and extracting features from the database table and the examples based on the associated ontology. The method further includes training a classifier based on the examples and the extracted features, and applying the classifier to the database table to obtain a semantic query result. The method also includes outputting the semantic query result to a user interface, and requesting user feedback of satisfaction with the semantic query result. The method additionally includes updating the classifier and the semantic query result iteratively in response to the user feedback.

Abstract: At least one processor may be operatively coupled to a plurality of memories and a node cache and configured to walk nodes of a per-pattern non-deterministic finite automaton (NFA). Nodes of the per-pattern NFA may be stored amongst one or more of the plurality of memories based on a node distribution determined as a function of hierarchical levels mapped to the plurality of memories and per-pattern NFA storage allocation settings configured for the hierarchical levels, optimizing run time performance of the walk.

Abstract: A processing device receives a request to create a report. The processing device generates one or more questions pertaining to a decision tree, the decision tree linking one or more attributes to one or more corresponding incident codes. The processing device displays one or more answers corresponding to the one or more questions. The processing device utilizes the one or more answers to traverse the decision tree to arrive at more questions. Responsive to the processing device determining that the traversal of the decision tree results in an arrival at an incident code, the processing device generate a report template using the determined incident code.

Abstract: A virtual file system is provided. Results are received of a first search for files related to current context of a user of the virtual file system, the files being stored on physical media and/or other virtual file systems. The results of the first search are organized into contextually significant virtual folders of the virtual file system. A first entry is recorded into a history of path mappings which map location of the files in the virtual folders to locations of the files on the physical media. Results are received of a second search for files related to an updated context of the user of the virtual file system. The organization of contextually significant virtual folders is updated based on the results of the second search, and a second entry is recorded into the history of path mappings based on the updated organization.

Abstract: At least one per-pattern non-deterministic finite automaton (NFA) may be generated for a single regular expression pattern and may include a respective set of nodes. Nodes of the respective set of nodes of each per-pattern NFA generated may be distributed for storing in a plurality of memories based on hierarchical levels mapped to the plurality of memories and per-pattern NFA storage allocation settings configured for the hierarchical levels, optimizing run time performance for matching regular expression patterns in an input stream.

Abstract: A system and method for tracking event occurrences among applications executing on a mobile device is provided. When an action is initiated, the first application generates a first notification indicator and records it with a notification server. When the action is performed by, for example, a second application, the second application generates a second notification indicator and registers it with the notification server. The notification server may then notify the first application or other entities of the occurrence of the action.

Abstract: A data processing method and a computer system. The computer system may perform discretization processing on a data sample to obtain a data sample in a matrix form, train the data sample in the matrix form according to a preset classification method to obtain a classification rule set, and after converting the classification rule set into a classification rule set that can be recognized by a data decision-making platform, provide the classification rule set to the data decision-making platform, so that the data decision-making platform can perform data decision-making according to the classification rule set that is obtained by the computer system by conversion and can be recognized by the data decision-making platform. All the foregoing processes are automatically completed by the computer system, which avoids human participation.

Abstract: The embodiment of this disclosure may include a rule engine that adds a plurality of objects into a working memory, and processes the plurality of objects through a plurality of rules stored in a rule repository. Then, the rule engine may create a rule network comprising a root node and a child node based on the plurality of rules, and associate the root node with a predetermined list of object references. The rule engine may build a multi-object sub-token based on the plurality of objects that satisfy the predetermined list of object references. Then, the rule engine may pass the multi-object sub-token from the root node to the child node.

Abstract: A computer-implemented method of increasing the online conversion rate of potential users to a computer-hosted service is described. The method includes a computing device receiving a browser request from a potential user, the computing device receiving user-specific data as part of the browser request. The computing device inputs the user-specific data into a conversion model executed by the computing device and outputs a conversion score for the potential user based on the model. The computing device sends to the browser a marketing intervention if the conversion score falls below a pre-determined threshold value.

Abstract: An approach is provided in which a knowledge manager locates centroids in a high-dimensional vector space that are closest to a new image feature set and performs nearest neighbor searches on feature sets included in clusters corresponding to the located centroids. The knowledge manager then selects feature sets closest to the new image feature set based on the nearest neighbor searches and in turn, marks images corresponding to the selected closest features sets as similar images to a new image corresponding to the new image feature set.

Abstract: Detecting a denial-of-service attack on a graph database is provided. In response to receiving a request to process a graph query on the graph database from a client device via a network, a graph query pattern of the graph query is determined. In response to determining that the graph query pattern of the graph query matches a stored graph query pattern that lead to a previous denial-of-service attack on the graph database, the graph query is identified as the denial-of-service attack on the graph database. Then, the request to process the graph query is denied by dropping the graph query.