Abstract: The intelligent automated assistant system engages with the user in an integrated, conversational manner using natural language dialog, and invokes external services when appropriate to obtain information or perform various actions. The system can be implemented using any of a number of different platforms, such as the web, email, smartphone, and the like, or any combination thereof. In one embodiment, the system is based on sets of interrelated domains and tasks, and employs additional functionally powered by external services with which the system can interact.

Abstract: Recycling of an electrochemical energy storage device is provided. A remaining charge on the electrochemical energy storage device is determined. An impedance profile of the electrochemical energy storage device is determined for the remaining charge. The impedance profile includes an internal impedance of the electrochemical energy storage device at different charge levels from the remaining charge to a complete discharge. A variable discharge load is applied on the electrochemical energy storage device until the complete discharge. The variable discharge load varies with the internal impedance of the electrochemical energy storage device at the different charge levels.

Abstract: A computing device receives a request requesting a screening design for an experiment. The device obtains, for the screening design, factors for screening in the experiment. A first factor is a categorical factor with a first set of candidate inputs comprising at least three candidate inputs in the experiment. A second factor is a continuous factor with a second set of candidate inputs comprising candidate input options within range(s) for the second factor. The device receives an indication of a run size that is a user-requested quantity of runs for the screening design. The device generates the screening design based on the run size. The device outputs the screening design. The screening design comprises runs of a quantity based on the user-requested quantity of runs for the screening design. The runs comprise the first set of candidate inputs and at least three inputs of the second set of candidate inputs.

Abstract: A boundary learning optimization tool for training neural networks with accurate models of parameterized flexure using a minimal number of numerically generated performance solutions generated from different design instantiations of those topologies. Performance boundaries are output by the neural network in optimization steps, with geometric parameters varied from smallest allowable feature sizes to largest geometrically compatible feature sizes for given constituent materials. The plotted performance boundaries define the design spaces of flexure systems toward allowing designers to visually identify which geometric versions of their synthesized topologies best achieve desired combinations of performance capabilities.

Abstract: Aspects of the present disclosure provide systems, methods, and computer-readable storage media that support automated summarization of documents using machine learning and artificial intelligence. The summaries include document category-specific summaries for different categories of documents. To illustrate, a document processing device may receive input data representing a document and provide first feature data based on the input data to one or more machine learning (ML) models to select a document category of a plurality of predefined document categories. The document processing device may provide second feature data based on the input data to a second set of ML models associated with the selected document category to generate annotation data associated with the document. The document processing device may provide the annotation data to a third set of ML models to generate a summary of the document, and the document processing device may generate an output based on the summary.

Abstract: Various examples are directed to systems and methods for facilitating fund transfers. A fund transfer system may access first training data comprising a first plurality of fund transfer records and train a computerized model, using the first training data, to generate a trained computerized model. The fund transfer system may use the computerized model to execute a plurality of fund transfer requests using the trained computerized model. The fund transfer system may access second training data comprising a second plurality of fund transfer records describing fund transfers executed in response to the plurality of fund transfer requests and re-train the computerized model using the second training data to generate a re-trained computerized model. The fund transfer system may execute an additional plurality of fund transfer requests using the re-trained computerized model.

Abstract: There is provided a computer implemented method for the automated analysis or use of data, to answer questions, comprising the steps of: (a) storing in a non-transitory storage medium a structured, machine-readable representation of data that conforms to a machine-readable language, in which the machine-readable language uses a shared syntax across factual statements, queries and reasoning, and uses nesting of nodes and passages, as an unambiguous syntax; where the data relates to parts of documents stored in a document store; (b) automatically processing the structured, machine-readable representation of data to answer questions, in which a user's query is automatically translated into the machine-readable language and a system responds to the user's query by utilising the machine-readable language translation of the query.

Abstract: Provided are techniques for data analysis and rule generation for providing a recommendation. A recommendation structure is built from features of data, where the recommendation structure comprises a plurality of rules, and where each rule of the plurality of rules is associated with a recommendation. The recommendation structure is sent to a model. A feature set comprising a feature and one or more related features is created from the features. In response to determining that a feature worthiness score of the feature set exceeds a threshold, the feature set is input to the model. A rule of the plurality of rules is received from the model, where the rule includes the feature, the one or more related features, and the associated recommendation. In response to receiving a set of values for the feature and the one or more related features, the rule is applied to the set of values to provide the recommendation.

Abstract: There are provided a method and a system for selecting an optimal synchronization broker for each workload. A system for selecting an optimal synchronization broker for each workload according to an embodiment includes: a storage unit including a database that contains specialist recommendation information including information on a correct protocol that is recommended by a specialist with respect to a service specification and data transmission requirements; and a processor configured to determine an optimal in-bound protocol and an optimal out-bound protocol according to the data transmission requirements through a decision tree model that is trained by using the specialist recommendation information as training data.

Abstract: Certain aspects involve building timing-prediction models for predicting timing of events that can impact one or more operations of machine-implemented environments. For instance, a computing system can generate program code executable by a host system for modifying host system operations based on the timing of a target event. The program code, when executed, can cause processing hardware to a compute set of probabilities for the target event by applying a set of trained timing-prediction models to predictor variable data. A time of the target event can be computed from the set of probabilities. To generate the program code, the computing system can build the set of timing-prediction models from training data. Building each timing-prediction model can include training the timing-prediction model to predict one or more target events for a different time bin within the training window. The computing system can generate and output program code implementing the models' functionality.

Abstract: Systems, programs, non-transitory computer readable mediums, and methods of managing multiple and concurrent online advertising campaigns to eliminate user fatigue are disclosed. In particular, a campaign management server generates multiple target lists of users from a data warehouse for a plurality of pre-defined online advertising campaigns. The users on the target lists are selected to receive electronic communications, such as email or text, containing advertisements based upon target profiles associated with the campaigns as determined by marketing objectives. The advertising campaigns are prioritized such that users on a target list of a higher prioritized campaign are suppressed from lower prioritized campaigns in order to insure that the users receive a predetermined number of electronic communications within a set time frame.

Abstract: The present disclosure describes techniques of implementing a collaborative advertising mechanism. The techniques comprise receiving a plurality of pieces of content associated with a mission event from a first plurality of client computing devices associated with a first plurality of users, evaluating the plurality of pieces of content based on one or more predetermined rules of the mission event and information indicative of viewer reactions to the plurality of pieces of content, determining at least one subset of the plurality of pieces of content based on a plurality of evaluation results corresponding to the plurality of pieces of content and user input from a client computing device associated with one of a second plurality of users, and distributing the at least one subset of the plurality of pieces of content.

Abstract: A device may receive network protocol data identifying a network protocol trace associated with network devices of a network, and may divide the network protocol trace into multiple segments. The device may identify a set of segments, in the multiple segments, that includes a first segment and second segments related to the first segment, and may process the multiple segments, in parallel, to determine first results data corresponding to the multiple segments. The device may process the second segments, in parallel, to determine second results data, and may combine the first results data and the second results data to generate final results data, wherein the final results data indicate utilization by the network devices of a network protocol associated with the network. The device may perform one or more actions based on the final results data.

Abstract: A method and a system process a stream of data in parallel across a plurality of nodes. The log processing system has a log module, a query language module, and a query processing module. The log module receives and organizes the stream of data into a sequential and nested data structure. The query language operator module defines operators that operate on the sequential and nested data structure. The query processing module processes in parallel across a plurality of nodes a query based on an operator on the stream of data.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for providing knowledge panels with search results. In one aspect, a method includes receiving a query. Search results that are responsive to the query are obtained. A first set of factual entities referenced by the query are identified. A particular factual entity is selected from the first set. It is determined that a knowledge panel for the particular factual entity is to be provided with the search results based, at least in part, on content of the knowledge panel and characteristics of the search results. The knowledge panel can include at least one content item, for the selected factual entity, received from a first resource and at least one content item, for the selected factual entity, received from a second resource different than the first resource. The knowledge panel is provided.

Abstract: A method, apparatus, and terminal for transmitting a message in a multiplayer game, and a medium are provided, belonging to the field of human-machine interaction. The method includes: displaying a first user interface of the multiplayer game, the multiplayer game providing a virtual environment for at least two teams of virtual characters to conduct an online battle; displaying a warning transmitting control in a predetermined region on the first user interface in response to that an event associated with a virtual character in the virtual environment satisfies a warning condition, the warning transmitting control being configured to transmit a warning message corresponding to the event; and transmitting the warning message to a second terminal in response to a transmitting operation on the warning message, the first account and the second account having a teammate relationship.

Abstract: Described herein are embodiments for machine-generating and naming ontologies for for-sale items. A neural network may be used to train information describing for-sale items into feature vectors that describe the for-sale items. These feature vectors may be sorted into clusters based on their relative proximity using clustering algorithms. The resulting clusters may be sub-divided into smaller clusters depending on the precision used in the clustering algorithm. The set of clusters may form a hierarchical data structure where each level has clusters determined at a certain precision and each lower level sub-divides those clusters. The clusters may be named based on the most salient facets that describe the for-sale items in the clusters.

Abstract: Apparatuses, systems, and techniques for detecting that one or more computer programs executed by a host device are subject to malicious activity using a machine learning (ML) detection system. An integrated circuit is coupled to physical memory of a host device via a host interface. The integrated circuit hosts a hardware-accelerated security service to protect one or more computer programs executed by the host device. The security service extracts a set of features from data stored in the physical memory, the data being associated with the one or more computer programs. The security service determines, using the ML detection system, whether the one or more computer programs are subject to malicious activity based on the set of features. The security service outputs an indication of the malicious activity responsive to a determination that the one or more computer programs are subject to the malicious activity.

Abstract: A telecommunication network management system. The system comprises an incident report management application that creates incident reports pursuant to alarms on network elements of a telecommunication network and wherein one of the incident reports is associated with a large-scale event (LSE), wherein the LSE incident report identifies alarms at a plurality of different network elements as associated with the LSE; and a network operation center (NOC) automation application that analyzes alarms on a plurality of network elements that are not yet associated with the LSE incident report and, based on analyzing a first alarm on a first network element of the plurality of network elements not yet associated with the LSE incident report, based on a location of the first network element, and based on the alarms associated with the LSE incident report, modifies the LSE incident report to associate the first alarm to the LSE.

Abstract: Systems and methods are provided for automating the process of generating image metadata related to a vehicle and damage sustained by the vehicle during a collision event by using image analysis tools employing machine learning algorithms. The image with collision metadata renders the image capable of being analyzed using content-based searching.

Abstract: In the object detection device, the plurality of object detection units output a score indicating a probability that a predetermined object exists, for each partial region set with respect to image data inputted. The weight computation unit computes a weight for each of the plurality of object detection units by using weight computation parameters and based on the image data. The weights are used when the scores outputted by the plurality of object detection units are merged. The weight redistribution unit changes the weight for a predetermined object detection unit, among the weights computed by the weight computation unit, to 0 and output the weights. The merging unit merges the scores outputted by the plurality of object detection units for each of the partial regions, by using the weights computed by the weight computation unit and including the weight changed by the weight redistribution unit.

Abstract: A computer implemented method of allocating a set of communications network resources to resource consumers in a digital communications system can include generating a set of multiple allocation schemes; iteratively applying a genetic algorithm to the set of allocation schemes to generate, at each iteration, a new set of allocation schemes as a generation of allocation schemes based on a preceding generation; and, responsive to a predetermined stopping condition for the iteration, assigning resource consumers to resources in the communications system in accordance with an allocation scheme in a most recent generation determined to satisfy a ranking condition.

Abstract: A system and method to authenticate users on a computing system using a free text behavioral biometric method by recording on the computer system a dataset for each user to be authenticated to create a user profile for each user to be authenticated, each data set comprising a plurality of free-text keystrokes entered by a respective user on a computer that is part of the computing system, and storing each user profile in the memory, subsequently collecting the keystrokes of a user to be authenticated as the user enters text on a keyboard connected to the computing system, creating a plurality of graphs based on the collection of keystrokes entered by the user and calculating n instance based tail area density (ITAD) metric, and then combining the ITAD metric for each graph duration into a single similarity score.

Abstract: There is provided a computer implemented method for the automated analysis or use of data, to answer questions, comprising the steps of: (a) storing in a non-transitory storage medium a structured, machine-readable representation of data that conforms to a machine-readable language, in which the machine-readable language uses a shared syntax across factual statements, queries and reasoning, and uses nesting of nodes and passages, as an unambiguous syntax; where the data relates to parts of documents stored in a document store; (b) automatically processing the structured, machine-readable representation of data to answer questions, in which a user's query is automatically translated into the machine-readable language and a system responds to the user's query by utilising the machine-readable language translation of the query.

Abstract: In variants, a system for automatically prioritizing content provided to a user can include and/or interface with any or all of: a set of content, a set of models, a set of processing and/or computing subsystems, and a set of messaging platforms and/or messaging interfaces. In variants, a method for automatically prioritizing content provided to a user can include receiving inputs from a set of users and/or processing the set of inputs to determine a set of content recommendations. The method can optionally further include providing content recommendations to a user and/or training and/or updating a set of models.

Abstract: Techniques are described for locating user devices in an indoor environment based at least on a building topology model. The techniques include detecting a presence of a user device in a building. The building may include ingress and egress points connecting defined spaces within the building. The locations of the individual ingress and egress points are identified based at least on the movement data of the user device. A building topology model may be generated using the locations of the individual ingress and egress points. To locate the user device at a given timestamp, one or more of the ingress and egress points passed through by the user device may be identified. The location of the user device may be determined based at least on the locations of the one or more ingress and egress points passed through by the user device mapped to the building topology model.

Abstract: Techniques are disclosed for systems including techniques for multi-factor modelling for training and utilizing chatbot systems for natural language processing. In an embodiment, a method includes receiving a set of utterance data corresponding to a natural language-based query, determining one or more intents for the chatbot corresponds to a possible context for the natural language-based query and associated with a skill for the chatbot, generating one or more intent classification datasets, each intent classification dataset associated with a probability that the natural language query corresponds to an intent of the one or more intents, generating one or more transformed datasets each corresponding to a skill of one or more skills, determining a first skill of the one or more skills based on the one or more transformed datasets and processing, based on the determined first skill, the set of utterance data to resolve the natural language-based query.

Abstract: An apparatus and methods for determining a resource distribution are provided. The apparatus includes a processor and a memory connected to the processor. The memory contains instructions configuring the processor to receive a first datum from a user device, where the first datum describes a first activity pattern of the user device, receive a second datum from a client device, where the second datum describes a second activity pattern of the user device, and to retrieve a third datum from the memory, where the third datum describes a prioritization value for adjusting the first activity pattern to match a threshold value. The processor may classify data to a label based on the prioritization value, where classifying includes modifying a sequence of activities in the first activity pattern and adjusting the second activity pattern.

Abstract: Disclosed embodiments relate to extracting classification information from input text.

Abstract: A battery diagnosing technology capable of effectively diagnosing a state of a secondary battery using a charge and discharge signal extracted from the secondary battery, including memory to store a positive electrode reference profile and a negative electrode reference profile for charge or discharge of a reference battery, a voltage sensor to measure a voltage of a target battery during a charge or discharge process, and a processor to generate a plurality of charge and discharge measurement profiles based on voltages measured at a plurality of different time points, compare each of the generated charge and discharge measurement profiles with a simulation profile obtained from the positive and negative electrode reference profiles, and determine positive and negative electrode adjustment profiles for each of the generated charge and discharge measurement profiles so that an error between each charge and discharge measurement profile and the simulation profile is within a predetermined level.

Abstract: Systems and methods related to prediction-based resource orchestration in a service fabric are described. An example method for reducing an interruption rate associated with a customer application offered as a collection of services includes predicting one or more quiet time periods associated with each of the service replicas associated with a service fabric, where each of the one or more quiet time periods corresponds to a low value of a predicted load specifying a consumption of a metric by a respective service replica on a given node. The method further includes during the one or more quiet time periods predicted by a trained machine learning model, performing an impact-less failover for one or more of the service replicas by scheduling a move for the one or more service replicas from a first node associated with the service fabric to a second node associated with the service fabric.

Abstract: Various examples of improving an in-memory graph query engine using a persisted storage component are provided. The method includes updating data stored in an in-memory graph query engine and, based on updating the data, converting the data to a plain text form that may be more efficiently stored in the persistent storage component. The method further includes updates to additional in-memory graph query engines from the persistent storage component such that in-memory data stored in the graph query engines is synchronized.

Abstract: Systems and methods for searching using machine-learned model-generated outputs can provide a user with a medium for generating a theoretical dataset that can then be matched to a real world example. The systems and methods can include selecting a plurality of terms, which can be utilized to generate a prompt input that can be processed by a dataset generation model to generate a plurality of model-generated datasets. A selection can then be received that selects a particular model-generated database to utilize to query a database.

Abstract: Techniques of generating input for a kernel-based machine learning system that uses a kernel to perform classification operations on data involve generating unbiased estimators for gaussian kernels according to a new framework called Structured Orthogonal Random Features (SORF). The unbiased estimator KSORF to the kernel involves a linear transformation matrix WSORF computed using products of a set of pairs of matrices, each pair including an orthogonal matrix and respective diagonal matrix whose elements are real numbers following a specified probability distribution. Typically, the orthogonal matrix is a Walsh-Hadamard matrix, the specified probability distribution is a Rademacher distribution, and there are at least two, usually three, pairs of matrices multiplied together to form the linear transformation matrix WSORF.

Abstract: Systems and methods for generating and actively improving clinical queues are provided. In one embodiment, a method includes generating, with a plurality of predictive models, a plurality of risk scores for each individual a plurality of individuals based on medical claims of each individual, transmitting a clinical queue to a client device associated with a healthcare provider, the clinical queue comprising a list of individuals prioritized for healthcare intervention based on the plurality of risk scores, receiving feedback from the client device regarding the clinical queue, and updating at least one predictive model of the plurality of predictive models based on the feedback. In this way, members may be identified for intervention in a timely manner, multiple assessment methods may be combined to generate clinical queues, and the assessment methods may be actively improved over time.

Abstract: Disclosed herein are systems and methods for selection of a model to describe a user. In one aspect, an exemplary method comprises, creating data on preferences of the user based on previously gathered data on usage of a computing device by the user and a base model that describes the user, wherein the base model is previously selected from a database of models including a plurality of models, determining an accuracy of the data created on the preferences of the user, wherein the determination is based on observed behaviors of the user, when the accuracy of the data is determined as being less than a predetermined threshold value, selecting a correcting model related to the base model, and retraining the base model, and when the accuracy of the data is determined as being greater than or equal to the predetermined threshold value, selecting the base model to describe the user.

Abstract: A system includes a data collection engine, a plurality of items including radio-frequency identification chips, a plurality of third party data and insight sources, a plurality of interfaces, client devices, a server and method thereof for preventing suicide. The server includes trained machine learning models, business logic and attributes of a plurality of patient events. The data collection engine sends attributes of new patient events to the server. The server can predict an adverse event risk of the new patient events based upon the attributes of the new patient events utilizing the trained machine learning models.

Abstract: A system and method for performing a desired verb action involves administering units of memory having a set of non-mutable components in a knowledge base. The components are organized as a graph with nodes and edges extending between the nodes. The nodes correspond to the components and are representative of definitional knowledge and procedural knowledge of a model. The model has a component representative of a vocabulary of components including components representative of performable actions and components a performable action can act upon. A verb is located in the vocabulary satisfying a criteria of the desired verb action. The verb action is performed in a context of a domain of discourse. The domain of discourse includes a set of components the performable action can act upon. The domain of discourse includes the vocabulary.

Abstract: A method includes identifying a sequence of transformations to be performed on an input dataset via a user interface. The method also includes identifying a first context associated with the input dataset. The method further includes selecting a first one of multiple execution engines to be used to perform the sequence of transformations on the input dataset based on the first context. In addition, the method includes providing first code implementing the sequence of transformations to the first execution engine and executing the first code using the first execution engine to perform the sequence of transformations on the input dataset.

Abstract: A plurality of similar video pairs may be determined based on one or more similarity information types. Each video pair of the plurality of similar video pairs may include a first respective video and a second respective video. For each video pair, one or more similar scene pairs may be determined. Each of the one or more similar scene pairs may include a respective first scene from the first respective video and a second respective scene from the second respective video. An encoder may be trained using a contrastive learning model that contrasts a plurality of similar scene pairs with a plurality of random scenes. The plurality of similar scene pairs may include the one or more scene pairs for each video pair. One or more scene features of one or more other scenes of one or more other videos may be determined using the encoder.

Abstract: A system for an artificial intelligence alimentary professional support network for vibrant constitutional guidance includes a computing device. The system includes a diagnostic engine designed and configured to receive a biological extraction from a user and generate a diagnostic output based on the biological extraction. The system includes an advisor module designed and configured to receive a request for an advisory input, generate an advisory output using the request for an advisory input and the diagnostic output, and transmit the advisory output. The system includes an alimentary input module designed and configured to receive the advisory output, select an informed advisor alimentary professional client device as a function of the request for an advisory input, and transmit the at least an advisory output to the informed advisor alimentary professional client device.

Abstract: A document creation system for creating documents corresponding to each case and falling into multiple document categories includes an input item tag creation configured to create input item tags, an input item tag list management configured to manage a list of the input item tags, and a tag-attached document creation configured to create a document using the input item tags.

Abstract: Disclosed are systems, methods, and non-transitory computer-readable storage media for managing projects in a content management system. In some embodiments, a content management system can generate a graphical user interface that presents a centralized view of a project. For example, the project can include project members, content items, tasks assigned to project members, communications between project members and activity history for the project. The graphical user interface can present this project data (e.g., project members, content items, tasks, communications, activity, etc.) so that a project member can easily and quickly view multiple aspects of the project.

Abstract: A method is disclosed. The method is implemented by a robot engine that is stored as program code on a memory of a system. The program code is executed by a processor of the system, which enables robotic process automations of the robot engine. The processor is communicatively coupled to the memory within the system. The method includes initiating a guided operation of a platform presented by the system and monitoring the guided operation to observe an interaction with the platform or to receive a direct input by the robot engine. The method also includes executing a backend operation with respect to the interaction or the direct input.

Abstract: A method comprises reading data from a source database, identifying one or more data types corresponding to the source database, identifying a destination database for the data, and identifying one or more data types corresponding to the destination database. In the method, a destination database model to use in connection with writing the data in the destination database is generated. The generation of the destination database model is based at least in part on the one or more data types corresponding to the destination database, and is performed using one or more machine learning algorithms.

Abstract: A corpus of textual data records, labeled by experts as corresponding to a defined characteristic, that comprise descriptions of problems with an item are collected. A language model generates a plurality of n-grams from the corpus. Frequently occurring n-grams are analyzed using a zero-shot learning model to determine similarity to the defined characteristic. N-grams highly similar to the defined characteristic may be selected as defined phrases. N-grams highly similar to another characteristic may also be selected to reduce false positives. The zero-shot model may also be used to determine a weighting factor for each defined phrase for each record. A relevance score is determined for a record by multiplying the weighting factors for each phrase that has a similarity score relative to the record above a threshold based on the expert labeling. The relevancy score may be used to automatically diagnose problems with the item.

Abstract: Disclosed are systems and methods for improving interactions with and between computers in content providing, searching and/or hosting systems supported by or configured with devices, servers and/or platforms. The disclosed systems and methods provide a novel framework that automatically generates and dynamically updates an interactive user interface (UI) that comprises digital information related to multiple processes and operations. The UI provides uniform functionality across platforms, devices and/or services being utilized to view and/or interact with the UI and/or interface objects (e.g., tiles) included therein. The UI provides a dynamic mechanism for assets to be controlled, as well as mechanisms to compare the data of different assets by which certain assets can be subsequently manipulated.

Abstract: Provided is a method, performed by a web browser, for identifying and displaying content, the method including receiving a webpage including text, comparing the text to titles of media content in a media content database, based on the comparison, identifying a subset of text as a match to a title of a matching media content, based on identifying the subset of text, modifying a display of the webpage by inserting a visual indicator into the webpage in proximity to the subset of text, or modifying the display of the subset of text, detecting an interaction of a user-controlled input with the inserted visual indicator or the modified display of the subset of text, and displaying a popup interface over a portion of the webpage, the popup interface displaying additional information about the matching media content and a selectable user-interface element to play the matching media content.

Abstract: The present disclosure is directed to systems and methods for enriching data. Specifically, the systems and methods disclosed enable the enrichment of data via matching, identifying composite data records, and utilizing Reference Source datasets. In one example aspect, Customer data is tokenized and then subsequently transmitted to a third-party Consolidation Platform. The Customer tokens may comprise multiple token records, wherein the multiple token records are displayed in the form of a bitmap. The bitmap may indicate which attributes in a Customer record may be present or absent. The composited Customer token records may then be matched to a Reference Source token set, wherein the matching analysis identifies missing data attributes in the Customer token set that the Customer may or may not already possess. The missing data attributes may be populated and/or updated in a Customer environment based on the Reference Source token set.

Abstract: Methods, systems, and computer program products for providing a contextual dialogue framework over dynamic tables are provided herein. A computer-implemented method includes maintaining a context space for a natural language conversation of a user, wherein the context space comprises a dynamic set of one or more tables used for processing at least one query of the natural language conversation; obtaining an additional table associated with an additional query of the natural language conversation; discovering one or more implicit links between the additional table and the dynamic set of tables; updating the context space with the one or more implicit links; and answering the additional query based at least in part on the updated context space.