Abstract: Systems and methods for modeling higher-level metrics from graph data derived from already-collected but not yet connected data are disclosed. A method includes extracting a first set of actor-related data, a second set of object-related data, and a third set of temporal data from the set of the already-collected but not yet connected data representative of a unit-level contribution to the target activity. The method further includes generating graph data for a graph using the set of the already-collected but not yet connected data, where each of the plurality of nodes of the graph corresponds to the actor or the object, and where an attribute associated with each of the plurality of edges of the graph corresponds to a measurement associated with the target activity. The method further includes modeling a relationship between graph attributes associated with the graph data and a higher-level metric associated with the target activity.

Abstract: In an embodiment, a method includes accessing, by a processor configured within a device, a central system that provides trained data and crowd-sourced data to be used to schedule a plurality of medical services and treatment options. A module is configured to receive the trained data and crowd-sourced data from the central system, and pass the trained data and crowd-sourced data to an application, and provide predictive capabilities to the application based on the trained data and the crowd-sourced data. The processor uses the application to provide scheduling intervals for a series of medical services and treatments at one or more medical stations in real-time. Another device is connected to the first device, wherein the other device is configured to access the application and identify the scheduling intervals, and request updates and changes to the scheduling intervals in real-time.

Abstract: Traditional blockchain monitoring systems have the disadvantage that they are capable of monitoring only a single blockchain ecosystem, as data from different blockchain networks running on different blockchain ecosystems may be heterogeneous in nature and poses associated data processing and interpretation challenges. The disclosure herein generally relates to blockchain monitoring, and, more particularly, to a method and system for monitoring blockchain networks belonging to different blockchain ecosystems. The system transforms the heterogeneous data to a homogeneous format, and then processes the data to identify one or more events. The system then identifies an action to be triggered in response to a determined event, which is then triggered by the system.

Abstract: Disclosed are a method and an apparatus for managing a user profile. A user profile management method performed by a server according to an example embodiment includes creating a plurality of profiles corresponding to a user account, receiving a view request for a profile of the other user account in a predetermined relationship with the user account from a user terminal logged in with the user account, providing a UI of a profile of the other user account including an interfacing object regarding the profile of the user account to the user account, receiving an input for selecting a profile to be displayed on the other user terminal logged in the other user account, among a plurality of profiles corresponding to the user account through the interfacing object, and matching the other user account with the selected profile.

Abstract: A social identity system has a collection of physical objects displayed under control of a specific enterprise, a data repository storing, as a virtual object, at least a name and a description of each physical object in the collection, each virtual object associated with a unique Social Identity of Objects (SIO) code, a broad variety of digital information, entered as digital files by registered members, each instance associated with a unique SIO code, and associated by SIO codes, with physical objects in the collection. A portion of the information defined by association with one of the physical objects comprises one or more of history, stories and opinions associated by SIO codes with the members contributing, the changing collection of information over time defining an evolving social identity of the particular one of the physical objects in the collection of physical objects.

Abstract: A method for generating for a subject a personalized playlist of sounds, notably songs, using the analysis of the subject's electroencephalographic signal, the method including the following steps: receiving at least one segment of electroencephalographic signal acquired from at least one electrode while the subject is listening to at least one proposed sound; extracting at least one EEG index from the electroencephalographic signal segment so as to characterize brain patterns correlated to the emotions evoked by the music and the level of appreciation of the sound; evaluating the valence of sounds listening on the basis of the EEG index; receiving a score of appreciation on the sound from the subject; including the sound in the personalized playlist (P) of the subject whenever the valence matches a predefined valence and/or the score of appreciation is higher than a predefined threshold.

Abstract: Described embodiments provide systems and methods for providing remote application action feed cards. A ticket can be received from a client device. The ticket can be indicative of an action of a remote application and the remote application can be accessible by a group of users. The device can receive information about the action identified in the received ticket from at least one user of the group of users in response to provision of a determined key and the received ticket to the group of users. The device can provide the received information to client devices of user of the group of users to identify actions of other users of the group of users.

Abstract: The present disclosure generally relates to systems, methods, and computer-readable media for developing and implementing workflows for a variety of data types. For example, systems disclosed herein may receive or otherwise generate a schema object on a schema system including a plurality of schema objects associated with different workflows. The schema object may include user interface behavior data indicating a content type and associated control type. The schema object may further include application programming interface (API) behavior data indicating a binding between a user interface engine and an API engine. The schema object may also include workflow behavior data indicating one or more services for processing the schema object. Moreover, systems described herein may deploy a plurality of parsers on a plurality of processing engines to enable flexibility and dynamic updates to content ingestion lifecycles.

Abstract: The present invention relates to a relation-enhancement knowledge graph embedding method and system, wherein the method at least comprises: performing collaborative coordinate-transformation on entities in the knowledge graph; performing relation core enhancement by means of relation-entropy weighting, so as to endow entity vectors with strong relation property; building an interpretability mechanism for a knowledge graph embedding model, and accounting for effectiveness and feasibility of the relation enhancement by proving convergence of the knowledge graph embedding model; and using a dynamic parameter-adjusting strategy to perform learn representation learning of to the vectors in the knowledge graph, and configuring deviation control to ensure accurate embedding.

Abstract: Methods, systems, and computer program products for software-defined database replication for a plurality of databases. Labels are applied to each of the plurality of databases and linking rules including conditions relating to the labels are used to define database replication links.

Abstract: Techniques for reducing CPU consumption in a federated search are disclosed. In some example embodiments, a computer-implemented method comprises determining an initial search scope by selecting a subset of searchable resources from a plurality of searchable resources based on interaction data of a user, with the initial search scope being defined by the selected subset of searchable resources, and the interaction data indicating online activity of the user directed towards past search results of past search queries submitted by the user. A federated search for a current search query is then performed using the initial search scope, with the federated search for the current search query being restricted to only the subset of searchable resources, and current search results for the current search query are generated based on the performing of the federated search.

Abstract: Systems and methods are provided for search result optimization using machine learning models. A search system uses machine learning models generate a target vector based on query features of a search query and a set of listing vectors based on listing features of listings identified as part of the search query. The target vector represents an estimated optimal listing for the search query and each listing vector represents a corresponding listing identified as part of the search query. The search system determines distances (e.g., Euclidian distance) between each listing vector and the target vector. The determined distances indicate how similar each listing is to the estimated optimal listing for the search query. The search system ranks the listings based on the distances such that listings that are similar to the estimated optimal listing are ranked higher than listing that are not similar to the estimated optimal listing.

Abstract: Systems and methods for neural machine translation are provided. In one example, a neural machine translation system translates text and comprises processors and a memory storing instructions that, when executed by at least one processor among the processors, cause the system to perform operations comprising, at least, obtaining a text as an input to a neural network system, supplementing the input text with meta information as an extra input to the neural network system, and delivering an output of the neural network system to a user as a translation of the input text, leveraging the meta information for translation.

Abstract: An apparatus includes an interface and a processor. The interface sends and receives data over a network. The processor uses the interface to transmit a first series of profiles to a first user that includes recommended profiles for a second user. The processor uses the interface to receive a selection from the first user of a profile corresponding to a third user. The processor uses the interface to transmit a second series of profiles to the third user that includes recommended profiles for the third user. The processor uses the interface to receive a selection from the third user of a profile corresponding to the second user. In response to receiving the selection from the first user of the profile corresponding to the third user and the selection from the third user of the profile corresponding to the second user, the processor enables communication between the second and third users.

Abstract: Systems and methods for lossy data compression using key artifacts and dynamically generated cycles are described, including receiving a data stream of relational data; detecting an artifact in the data stream associated with a critical point in the relational data; analyzing, by a processing device, the artifact to determine a set of artifacts associated with a complex event where the critical point is an endpoint of the complex event; calculating one or more cycle metrics based on the set of artifacts; generating a data structure associated with the complex event and cycle metrics; providing the data structure for marking a display of the relational data with the complex event based on the cycle metrics.

Abstract: Video and corresponding metadata is accessed. Events of interest within the video are identified based on the corresponding metadata, and best scenes are identified based on the identified events of interest. A video summary can be generated including one or more of the identified best scenes. The video summary can be generated using a video summary template with slots corresponding to video clips selected from among sets of candidate video clips. Best scenes can also be identified by receiving an indication of an event of interest within video from a user during the capture of the video. Metadata patterns representing activities identified within video clips can be identified within other videos, which can subsequently be associated with the identified activities.

Abstract: Systems and methods are described for a three-tiered artificial intelligence architecture that synchronizes processing statement deployment across diverse computer networks. The system may receive, at a user interface, a first request for a first recommendation. The first recommendation includes a set of standardized processing statements for implementing on a function. The system may input the first request into a first network component. The first network component includes first, second, and third models. The first model is trained to generate a library of standardized processing statements. The second model is trained to generate a plurality of standardized processing characteristic values for each standardized processing statement in the library. The third model is trained to generate recommendations of sets of standardized processing statements to functions. The system receives an output from the first network component and generates for display the first recommendation based on the output.

Abstract: Embodiments described herein include receiving an application flow defining logic for triggering automated actions for a candidate post on one or more web-based communication channels. An artificial intelligence (AI) powered web crawler may crawl a set of websites for target content. Responsive to identifying target content, machine learning may be leveraged to identify an entity name for an entity that is a subject of the target content and associate the entity with one or more event categories. Based on the event categories, a segment may be generated at runtime for the application flow where segment membership was not known at the time the application flow was defined or before application runtime.

Abstract: Techniques for propagation of deletion operations among a plurality of related datasets are described herein.

Abstract: Methods and systems for distributed cognition of digital content include receiving submissions from community members regarding a knowledge object. Each community member has a reputation value and each submission includes an evaluation value representing an evaluation of the knowledge object by the community member. A consensus evaluation is determined based on a calculated combination of the evaluation values in the submissions received and the reputation values of the respective community members who submitted the submissions. While submissions are being received, the consensus evaluation of the knowledge object is iteratively updated based on submissions received, being a calculated combination of the evaluation values in the submissions received and the reputation values of the respective community members who submitted the submissions.