Abstract: This disclosure describes techniques in which an artificially intelligent system includes a progressive machine learning model. In some examples, a system includes both a static and progressive model, each trained to make predictions or other assessments through machine learning techniques. The progressive model may be progressively updated, modified, and/or improved through additional training data or training examples, which may be derived from a local source and/or from one or more remote sources that may be chosen by a qualifier. The qualifier may be a human decision-maker that chooses, selects, and/or evaluates potential data or new training examples for use in updating the progressive model. The qualifier may, in other examples, be an artificially intelligent system trained to perform the functions of the qualifier.

Abstract: A mnemonic phrase management method. The method comprises: generating a random number having a first preset length and performing calculation on the random number; splicing the random number and data having a second preset length acquired from the random number calculation result to obtain a first spliced value; grouping the first spliced value according to a third preset length; sequentially searching an offset storage area for corresponding indexes according to values of the groups; obtaining mnemonic phrase starting offset addresses and mnemonic phrase lengths according to the indexes; and acquiring corresponding mnemonic phrases from a mnemonic phrase storage area according to the mnemonic phrase starting offset addresses and the mnemonic phrase lengths and sequentially storing the mnemonic phrases into a mnemonic phrase buffer. The present invention relates to the field of information security.

Abstract: An example operation may include one or more of storing a batch scoring engine and an application programming interface (API) for the batch scoring engine, receiving a trigger to perform a batch prediction process, reading input data from a source data store and executing, via the batch scoring engine, one or more predictive models on the input data to generate a predictive output and metadata associated with the predictive output, storing the predictive output and the metadata in a target data store, and updating the API with a location of the predictive output within the target data store and a location of the metadata within the target data store.

Abstract: Briefly, embodiments, such as methods and/or systems for creating and/or updating elements of a knowledge graph (KG), for example, are described.

Abstract: Systems and methods for artificial intelligence transaction priority control are presented. Transaction priority control may be provided in the context of online user accounts maintained by financial institutions. Transaction priority control may be obtained through querying transaction information from a database, applying a predictive model to determine a likely future transaction, assigning a priority score to the future transaction, and approving or denying the future transaction based on the priority score.

Abstract: A computing system identifies an incoming voice call from a user device to an agent device associated with the computing system. The computing system generates a transcription of the incoming voice call using one or more natural language processing techniques. The computing system extracts a problem description from the transcription. The problem description indicates a topic for the incoming voice call. A first machine learning model estimates a situation vector from the problem description. A second machine learning model identifies a pre-existing situation vector that closely matches the estimated situation vector. The computing system retrieves a situation description that corresponds to the identified pre-existing situation vector.

Abstract: The data analysis server manages first data configuration information for managing a correspondence of the learned data model, a raw data bucket that stores the raw data for generating the learned data model, and a curated data bucket that stores the curated data for generating the learned data model and second data configuration information for managing correspondences of the learned data model and the first storage area, the curated data bucket and the second storage area, and the raw data bucket and the third storage area, and gives an instruction to acquire snapshots of the second storage area that stores the curated data for generating the learned data model and the third storage area that stores the raw data for generating the learned data model to the data storage via the storage management server when the learned data model is generated.

Abstract: Systems and methods for using machine learning and rules-based algorithms to create a patent specification based on human-provided patent claims such that the patent specification is created without human intervention are disclosed. Exemplary implementations may: obtain a claim set; obtain a first data structure representing the claim set; obtain a second data structure; obtain a third data structure; and determine one or more sections of the patent specification based on the first data structure, the second data structure, and the third data structure.

Abstract: Techniques for context sensitive illustrated graphical user interface elements, comprising a social networking application. The social networking application may include, among other components, a social networking graphical elements management component to provide a list of recommended graphical element identifier information, in response to a request for the list of recommended graphical element identifier information, a context determination component to determine user context information representative of the at least one user context based at least partially on user communications intent information, user profile information, device location information, calendar event information, and/or external event information, and a graphical elements recommendation component to generate the list of recommended graphical element identifier information based at least partially on the user profile information, graphical elements promotion information, and/or the user context information.

Abstract: A computing system identifies an incoming voice call from a user device to an agent device associated with the computing system. The computing system generates a transcription of the incoming voice call using one or more natural language processing techniques. The computing system extracts a problem description from the transcription. The problem description indicates a topic for the incoming voice call. A first machine learning model estimates a situation vector from the problem description. A second machine learning model identifies a pre-existing situation vector that closely matches the estimated situation vector. The computing system retrieves a situation description that corresponds to the identified pre-existing situation vector.

Abstract: A data management method is provided. To-be-migrated base data in a first service data set is obtained, mirror data that are same as the base data are generated, and the base data to a second service data set are migrated. Incremental data obtained for the base data are recorded in the migration process of the base data. Adding processing is performed on the mirror data by using the incremental data, and the incremental data are migrated to the second service data set, when the migration process of the base data is completed. The mirror data and the incremental data in the first service data set are cleared when the migration process of the incremental data is completed.

Abstract: In an approach to deriving highly accurate models, one or more computer processors train a set of machine learning models utilizing a training set and a deep learning algorithm; generate one or more feedback data sets for each model in the set of trained models; rank each model in the set of trained models based on the generated feedback data sets; dynamically adjust one or more thresholds, that initiate a retraining or deployment of one or more ranked models, based, at least in part, on one or more production environment requirements; responsive to exceeding one or more adjusted thresholds, automatically deploy one or more ranked models to one or more deployment environments based, at least in part, on the ranking of the one or more trained models; responsive to not exceeding one or more adjusted thresholds, retrain each model in the set of trained models.

Abstract: A solution is proposed for ranking documents belonging to two different domains. A corresponding method comprises generating a descriptor for each of the documents; the descriptor comprises corresponding values and confidence indexes of multiple properties (of the corresponding document); the documents of a domain are ranked with respect to a document of another domain according to a comparison of their descriptors. A computer program product for performing the method are also proposed. Moreover, a computing system for implementing the method is proposed.

Abstract: A computer-implemented method applies labels to unlabeled public data for use by a global model. One or more processors train one or more local machine learning models with local private data to create one or more trained models. Processor(s) generate a label for each of the local private data using the one or more trained models, where each label describes the local private data, and then apply the label to unlabeled public data to create labeled public data. One or more processors then input the labeled public data into a global model that uses the public data.

Abstract: A device that includes an enterprise data indexing engine (EDIE) configured to obtain a set of sentences from a document, to associate one or more of the sentences with a first classification type, to associate one of the sentences with a second classification type, and to link the classified sentences together. The EDIE is further configured to determine a set of similarity scores between the classified sentences and a plurality of classification descriptions. The EDIE is further configured to identify a classification description that is associated with the highest similarity, to identify a token associated with the identified classification description, and to output the token.

Abstract: Systems and methods for dynamic computer modeling using incomplete data are provided. The system can yield a total score indicative of an accuracy and reliability of a model for a given application based on incomplete data. The system can receive one or more sets of datasets, classify each dataset among the set of datasets based on a classification component, and determine a normalized score for each dataset based on a value or values of each dataset. If a classification component does not comprise more than one dataset, then the system determines a classification component score for each dataset as the normalized score. If a classification component comprises more than one dataset, the system assigns a weighted data value to each dataset of the classification component. A classification component score is determined for each weighed dataset by applying the weighted data value to the normalized score for each weighed dataset.

Abstract: A device that includes an enterprise data indexing engine (EDIE) configured to receive a set of input sentences and to determine a set of similarity scores between the set of input sentences and a plurality of classification descriptions. The EDIE is further configured to identify a classification description that is associated with the highest similarity score and to identify a token that is associated with the identified classification description. The EDIE is further configured to link the identified token with the set of input sentences.

Abstract: Techniques are provided for generating and applying a granular attention hierarchical neural network model to classify a document. In various embodiments, data indicative of the document may be obtained (102) and processed (104) into a first layer of two or more layers of a hierarchical network model using a dual granularity attention mechanism to generate first layer output data, wherein the dual granularity attention mechanism weighs some portions of the data indicative of the document more heavily. Some portions of the data indicative of the document are integrated into the hieratical network model during training of the dual granularity attention mechanism. The first layer output data may be processed (106) in the second of two or more layers of the hierarchical network model to generate second layer output data. A classification label can be generated (108) from the second layer output data.

Abstract: Methods, systems, and computer-readable storage media for retrieving metadata associated with data stored within a database system of an enterprise, the metadata being provided in a first format and being used by the first system to store and access the data, providing a document including the metadata provided in an interoperable format, processing, by a deployer, the document to provide analytics engine metadata in a second format, the analytics metadata being stored in the second system and being consumable by the DB-based analytics engine to access the data from the database system of the enterprise, and retrieving, by the DB-based analytics engine, the data from the database system of the enterprise based on the analytics metadata to provide analytics data based on the data.

Abstract: A method for rendering context based information on a user interface includes receiving a user request to extract the context based information from a database. The database includes a plurality of documents and the request includes at least one search criteria required to determine a context of the user request. The method includes generating a list of documents corresponding to the context of the user request and rendering on a viewing portion of the user interface the list of documents corresponding to the context of the user request.

Abstract: The invention relates to a data standardization technology, and discloses an XBRL-based global data standardization platform system and a construction method thereof, so as to efficiently and conveniently integrate various types of data, and implement the data localization and globalization.

Abstract: A system includes a model repository comprising a plurality of models respectively being adapted to perform, when used by an analytical program, a computational task, in which a first database table is created in the database, the first database table having a predefined table structure that corresponds to the analytical program, a best-model of the plurality of models is stored in the first database table, and a request of a client device to perform the computational task and comprising input data is received. If the received request does not comprise a model-ID, the analytical program reads the model currently stored in the first table and uses the read model for performing the computational task on the input data.

Abstract: A data storage and retrieval system for a computer memory for maintaining a database for product life cycle support (PLCS database). A computer system receives data exchange packets comprising data fields and populated with data according to different respective database schema and selects optimal data from amongst the packets. A master data exchange packet is formed comprising common field headers and the optimal data in data fields of the master data exchange packet. The system maps the common field headers to corresponding field headers of the PLCS database schema, and loads the optimal data of the master data exchange packet into the PLCS database according to the mapped PLCS field headers.

Abstract: Aspects described herein may be used with local spreadsheet applications, web, and/or cloud-based spreadsheet solutions, to create complex custom software applications. Spreadsheets themselves lack the conceptual framework to be used as a platform tool to build custom or complex software applications. Using the methods and systems described herein using low-code/no-code techniques, a designer can create custom and/or complex software applications using one or more spreadsheets as the underlying blueprints for the software application. The resultant software application may be static/read-only, or may be interactive to allow users to dynamically add, delete, edit, or otherwise amend application data, e.g., via one or more online web pages or via a mobile application. Data transfer may be one-way or bi-directional between the blueprint spreadsheets and the resultant software application, thereby allowing amended data to be transferred from the software application back into spreadsheet form.

Abstract: A system, method and program product for stratigraphic layer identification using a stratigraphic knowledge base for machine learning. Reservoir data includes seismic data and well log data for a reservoir area. The well log data is processed to identify well stratigraphic layer features and the seismic data is processed to identify seismic stratigraphic layer features. A feature matching algorithm based on a stratigraphic knowledge base is selected to match the well stratigraphic layer features to the seismic stratigraphic layer features. The matched features are used to define a stratigraphic layer interpretation for the reservoir area and the interpretation is presented to a user.

Abstract: Methods and systems for document classification are provided. One method includes generating by a processor, a plurality of topics using content of a plurality of electronic documents, where each topic includes a plurality of words associated with the plurality of electronic documents; reducing by the processor, the plurality of topics to a subset of topics to represent the plurality of electronic documents based on a parameter indicating a property of each subset topic and separation between the subset topics; automatically generating by the processor, a tag for each subset topic, based on the tag's position within the subset topic; wherein each tag is an attribute of each subset topic; storing by the processor, the subset of topics with corresponding tags in a model data structure; and updating the model data structure by the processor based on one of a new topic and a new tag associated with an electronic document.

Abstract: Facet-based query refinement based on multiple query interpretations is provider through a process that includes receiving a query for querying documents, of a whole document set, that deviate by one or more facet values. The process generates different query interpretations from query text of the query. The process executes the different query interpretations to obtain resulting document sets. For each different query interpretation, the executing executes the query interpretation to obtain a resulting document set corresponding to that query interpretation, and identifies facet values represented in the resulting document set. The process builds and presents to a user a query refinement interface, presenting the different query interpretations and properties of the resulting document sets, as well as, for each of the one or more facet values, and relative to each other, facet value representation of the facet value in each of the resulting document sets.

Abstract: A method for distributed pod-editing may be performed by an enhanced pod editor, and may include the following steps: receiving a framework for a pod, wherein the framework identifies one or more content items already assigned to one or more slots in the pod by one or more pod editors; determining attributes of the content items already assigned to the pod in a native taxonomy of the enhanced pod editor; determining restrictions on the pod's slots based on the attributes of the content items already assigned to the pod and on the pod's editorial constraints; rejecting content items already assigned to the pod that violate the restrictions on the pod's slots (if any); identifying candidate content items that comply with the restrictions on the pod's unfilled slots (if any), and selecting candidate content items and assigning the selected content items to the pod's unfilled slots.

Abstract: An identifier (232) identifies an alternative product to an attended product getting attention from a user. A searcher (231) searches, when a search condition is given, a group of products satisfying the search condition. A first generator (233) generates a first search condition expected to obtain a search result containing the attended product and the alternative product. A verifier (234) verifies, based on an obtained first search result by the searcher (231) that has searched under the generated first condition, whether or not the first search condition is proper. A second generator (235) generates a second search condition that is the first search condition verified as proper and with an added or replaced condition of a price range that is different from a price range of the attended product. A presenter (240) presents an obtained second search result to the user by the searcher (231) that has searched under the generated second condition.

Abstract: An authorization policy recommendation method is provided. The method includes obtaining account data based on a cloud service, provided authorization policy data, and service data; and extracting an account feature, an authorization policy feature, and a service feature according to the account data, the provided authorization policy data, and the service data. The method further includes generating a combined feature based on the account data, the provided authorization policy data, and the service data; performing model training according to the account feature, the authorization policy feature, the service feature, and the combined feature, to generate a policy predictive recommendation model; and performing predictive recommendation according to context scenario information of a current account in the cloud service based on the policy predictive recommendation model, obtaining an authorization policy by screening, and recommending the authorization policy to the current account.

Abstract: In the pharmaceutical research and development process, it may be necessary to process large amounts of medical records or clinical literature, to ensure safety of patients consuming a drug. A pharmacovigilance system may assist in this process by efficiently and automatically processing medical records to extract information and relationships contained therein and may also form a preliminary assessment regarding a medical or clinical judgment. The pharmacovigilance system may automatically generate reports based on this information, which may be validated by trained clinicians and medical experts.

Abstract: Systems, methods, and computer-readable media are provided for graph data modeling. In accordance with one implementation, a method is provided that includes operations performed by at least one processor. The operations of the method include receiving raw data and determining a model for the raw data, wherein the model defines the graph structure for the raw data. The method also includes converting the raw data to fit the model, and generating at least a portion of a graph based on the raw data and the model, wherein the graph produces modeled data. The method also includes archiving the graph.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for providing filters from resource content. In one aspect, a system receives data identifying a set of resources that are determined to be responsive to a search query and extracts a set of keywords from the contents of the resources and related queries. The keywords are processed according to candidate selection criteria, and a set of candidate query filters are determined. The candidate filters may be used to filter the resources that are responsive to the query.

Abstract: In one example embodiment, a computer-implemented method is provided for caching data from an online resource based on social characteristics of users using the data. The method includes dividing the users into one or more social groups according to the social characteristics, and creating one or more cache databases corresponding to the one or more social groups, wherein data in each of the one or more cache databases are indexed by one or more user attributes identifying social characteristics of user used the data.

Abstract: Methods, systems, and devices are provided for authenticating API messages using PKI-based authentication techniques. A client system can generate a private/public key pair associated with the client system and sign an API message using the private key of the private/public key pair and a PKI-based cryptographic algorithm, before sending the signed API message to a server system. The server system (e.g., operated by a service provider) can authenticate the incoming signed API message using a proxy authenticator located in less trusted zone (e.g., a perimeter network) of the server system. In particular, the proxy authenticator can be configured to verify the signature of the signed API message using the public key corresponding to the private key and the same cryptographic algorithm. The authenticated API message can then be forwarded to a more trusted zone (e.g., an internal network) of the server system for further processing.

Abstract: Systems and methods for facilitating caching of programming data are provided herein, including receiving two or more programming data portions, storing the respective programming data portions, managing access to the storage component or the communication component based on programming data portions stored within the storage component, and generating a sleep signal based on a period of inactivity which exceeds an inactivity threshold. In one or more embodiments, caching of programming data may include determining a programming data set based on user profile data, parsing the programming data set into two or more programming data portions, converting respective programming data portions into a format based on a remote configuration, transmitting a first programming data portion of the respective programming data portions, and transmitting additional programming data portions of the respective programming data portions based on a sleep signal.

Abstract: The present invention provides a method and apparatus for representing content information. The method and apparatus for representing content information according to embodiment of the present invention notifies the user employing a mobile environment (mobile terminal or smart terminal) in a tactile, auditory, or visual manner about existence of contents having a score larger than or equal to a particular score within a predetermined distance to represented contents in a predetermined order and enables the user to perform a search for the contents desired by the user based on the user's input, providing such an advantage that the user can find the contents of interest intuitively without examining searched contents one after another.

Abstract: Mechanisms are provided for anonymizing data comprising a plurality of graph data sets. The mechanisms receive input data comprising a plurality of graph data sets. Each graph data set comprises data for generating a separate graph from graphs associated with other graph data sets. The mechanisms perform clustering on the graph data sets to generate a plurality of clusters. At least one cluster of the plurality of clusters comprises a plurality of graph data sets. Other clusters in the plurality of clusters comprise one or more graph data sets. The mechanisms also determine, for each cluster in the plurality of clusters, aggregate properties of the cluster. Moreover, the mechanisms generate, for each cluster in the plurality of clusters, pseudo-synthetic data representing the cluster, from the determined aggregate properties of the clusters.

Abstract: The claimed subject matter includes a system and method for attribution of search activity in multi-user settings. The method includes training a classifier to distinguish between machines that are single-user and multi-user based on activity logs of an identified machine. The identified machine is determined to be multi-user based on the classifier. A number of users is estimated for the identified machine. Activity of the users is clustered based on the number of users estimated. A similarity function is learned for the number of users estimated. The method also includes assigning new activity to one of the users based on the clustering, and the similarity function.

Abstract: An aggregation service aggregates extraction results from diverse named entity recognition (“NER”) services, which can help improve the quality of extracted information. In some cases, the aggregation service considers differences in entity type classifications when aggregating extraction results from different NER services. The aggregation service can also consider performance characteristics (e.g., error rates) for the different NER services. For example, the aggregation service receives extraction results generated for a document corpus according to an entity type schema for each of multiple different NER services, then aggregates the extraction results based at least in part on relations between entity types for the NER services. For a given annotation area, the computing system can identify hypotheses and rank the hypotheses according to an aggregation approach.

Abstract: Disclosed herein is a system and method for generating an enhanced index for documents contained in a knowledge base. Documents or configuration snapshots are tokenized and then passed through a number of filters. The filters modify the token stream to generate an enhanced token stream for the document by removing words from the stream and adding domain level knowledge to the tokens in the stream. The token stream is then added to the index for the document so that searches can be completed against the knowledge base when searches are generated from configuration snapshots or from inputted search queries.

Abstract: According to one embodiment, a system includes an interface and a processor. The interface receives, from a device, a request to access an application-store module, the device being associated with a first user. The processor determines a device type associated with the device; determines an operating system associated with the device; determines a user role associated with the first user; and determines, based on the device type, the operating system, and the user role, one or more applications. The interface communicates, to the device, a first set of information to be displayed on the device, the first set of information being associated with the one or more applications.

Abstract: A system and method of merging text analysis results. The system uses a set of three corrected, weakened Jaccard factors to determine whether the respective results of multiple text analysis operations are equal, subtypes of each other or associated with each other, in order to merge the results.

Abstract: A contextual community paradigm is engineered to define context between human and machine. This contextual community paradigm enables support of multiple taxonomies for any given object. Human and machine share context. The contextual community paradigm simplifies resolution of the user's intent, enabling automated interactions between human and machine spanning functions and applications. The paradigm facilitates real-time context resolution. The paradigm also resolves intent for the purpose of automating and assisting in the execution of tasks involving people, devices, and concepts, such as events and information.

Abstract: A data construct called a semcard is a semantic (meaning-based) software object including semantic meta-tags and meta-data that describes a target object or thing. A target object can be any type of digital or physical entity or identifier, or it can be tacit knowledge, such as ideas, concepts, processes or other data existing in a user's mind, provided that the user represents this knowledge in the semcard. A semcard embodies information about its own structure—rules, history, state, policies and goals regarding automation, display, access permissions, sharing and other operations of the semcard and any optional target object. It can also represent a semantic link between two semcards, or a semantically typed link or a standard Web hyperlink between a semcard and its referent target. A collection of semcards represents a knowledge network; single semcards, and knowledge networks, can be browsed, shared, searched, disseminated, manipulated, displayed, organized, and stored.

Abstract: The present invention is a method of organizing and processing data in a distributed computing system. The invention is also implemented as a computer program on a computer medium and as a distributed computer system. Software modules can be configured as hardware. The method and system organizes select content which is important to an enterprise operating said distributed computing system. The select content is represented by one or more predetermined words, characters, images, data elements or data objects. The computing system has a plurality of select content data stores for respective ones of a plurality of enterprise designated categorical filters which include content-based filters, contextual filters and taxonomic classification filters, all operatively coupled over a communications network.

Abstract: A system, method and article of manufacture that selects at least keyword from a taxonomy of a publication system; used the at least one keyword for performing data mining of a social network to detect conversations relating to products; compared elements of the conversations with functions of the publication system; and responsive to comparing, uses the elements of the conversation to change the taxonomy or the offering of products on the publication system. The conversations comprise posts relating to a product, the functions of the publication system comprise searches relating to the product, and changing the taxonomy comprises adding a category to the taxonomy.

Abstract: Methods and apparatus for analysis of semi-structured social media are described. A method comprises classifying a plurality of user-generated content entries into a plurality of categories based at least in part on an analysis of respective structured components of at least a subset of the plurality of entries. The method further includes determining, based at least in part on an analysis of additional components of entries of a particular category, a set of representative content elements of entries of the particular category, and generating a report that comprises one or more representative content elements of the particular category.

Abstract: Systems and methods are disclosed herein for providing search results, particularly product records from a product database. Products records have facet groups associated therewith and facet groups have probabilities associated therewith indicating the usefulness of the facet group as a way of organizing or filtering search results. For a query, relevant product records are identified. For facet groups present among the relevant product records entropy values are calculated based on a distribution of values for the attribute defining the facet group. The entropy value increases as the distribution of values becomes more uniform. The facet group probability and entropy value are combined to assign a score to the facet groups. The facet groups are ranked and selected according to the score and search results are presented with indicators of the facet groups to enable a user to manage the search results.

Abstract: Examples disclose systems and methods for recognizing objects. A method may be executable to receive a query from a robot. The query may include identification data associated with an object and contextual data associated with the object. The query may also include situational data. The method may also be executable to identify the object based at least in part on the data in the query received from the robot. Further, the method may be executable to send data associated with the identified object to the robot in response to the query.