Abstract: Disclosed herein are systems and methods of artificial intelligence learning systems. In some embodiments the artificial intelligence system presents options to users based on their life stage and personality profile. Family or group structures may be created within an application. Options may be created and presented based on the family structure such as chores may be assigned to children, money may be transferred between family members, and scores may be assigned to different users.

Abstract: A system and method for supporting identifying experts on arbitrary topics in an enterprise social network. An exemplary method can receive, at a node of a social network application, a plurality of content. The method can store the plurality of content in a database associated with the social network application. The method can index the plurality of content, resulting in an index of content, wherein the index of content includes a plurality of activity signals and a plurality of security values. The method can receive a request for a search for at least one expert on an arbitrary topic. The method can search the index of content for the at least one expert on the arbitrary topic, resulting in a plurality of search results. The method can next assign a weight for each of the plurality of search results based at least on the plurality of activity signals.

Abstract: Systems and methods are provided for performing context-based keyword searching using a search bar. Based on search terms received via the search bar, the system may be configured to provide suggested search parameters to associate with that search term. The suggested search parameters may each include a type of data and/or a filter to associate with the search term (e.g., name, phone number, date of birth, etc.). The one or more suggested search parameters may be identified based on the search term itself, a list of possible types of data or filters, a preliminary search of one or more datasets, a record of one or more previous searches performed, requirements associated with one or more searchable datasets, the format of user input received via the search bar, and/or one or more other factors.

Abstract: Systems are provided for managing defect data objects. A system stores a plurality of defect data objects that have been input to the system, and generates an issue item including one or more defect data objects that are selected from the stored defect data objects based on user input. The system determines similarity between the one or more defect data objects in the issue item and one or more of the stored defect data objects that are out of the issue item, based on comparison of one or more parameter values. The system determines one or more candidate defect data objects to be included in the issue item from the one or more of the stored defect data objects that are out of the issue item based on the similarity, and includes one or more of the determined candidate defect data objects in the issue item based on user input.

Abstract: A computer-implemented system for engaging automatic attention capture functionality of human neuronal structures by added transitory salient stimuli that draw user attention to parts of displayed documents, which stimulates involuntary neuronal interference with other image processing at no more than user-tolerable levels. After user initiated finding or displaying of document parts, when added visual salience is transitory and as presented, added motions are at the speeds presented, and when otherwise used in contexts presented in the disclosure, even extremely salient motion stimuli that involuntarily engage neuronal motion detection circuitry and thereby involuntarily capture attention in unique ways nevertheless stimulate interference with other visual processing at no more than user tolerable levels. Non-motion transitory visually salient ways of engaging automatic attention capture are also used in some circumstances.

Abstract: A method includes receiving readings from a plurality of Internet of Things (IoT) devices. The method identifies rules associated with the readings from the IoT devices and determines a three dimensional (3D) dataset based on the plurality of IoT devices, the readings and rules associated with the readings from the plurality of IoT devices. The method includes determining policies to be applied to routing of the readings based on rules for dividing the readings into subsets of the 3D dataset, and routing processing for subsets of the readings to be processed in parallel by processing units based on the policies. The method further includes processing the readings to generate a list of actions, and resolving the conflicts in the list of actions based on a multi-phase queue. The method also includes executing the actions.

Abstract: The measurement guide device is able to easily select the next measurement target on the basis of previously obtained measurement results. The measurement guide device includes a database, a similarity search section, and a next-point proposal section. The database stores a virtual measured signal and a measurement procedure that are obtained by simulation. The similarity search section extracts, from the database, virtual measured signals similar to measurement results obtained by a measurement device, and measurement procedures regarding the virtual measured signals. The next-point proposal section selects at least one measurement procedure from the measurement procedures obtained by the similarity search section, and determines the next measurement point.

Abstract: This disclosure relates generally to a system and method for creating unified personalized content for an individual user receiving communications from a given website across separate platforms and channels.

Abstract: Embodiments of the present specification disclose methods, apparatuses, and devices for transferring data assets based on a blockchain. One method includes: obtaining usage demand information of a data requestor for using original data, wherein the usage demand information indicates a demand of the data requestor for performing computations based on the original data; sending a usage authorization request for the original data to a data owner of the original data based on a decentralized identifier (DID) corresponding to the original data; receiving confirmation information of the usage authorization request from the data owner; processing the original data based on the usage demand information to obtain a processing result; transmitting the processing result to the data requestor; and generating a verifiable claim (VC) for recording usage information of the original data.

Abstract: The present disclosure relates to a large-scale and low-latency data retrieval and storage system for a multi-tenant, cloud-based application, such as a Quote-to-Cash application. Conventionally, such applications rely heavily on SQL databases, which have difficultly providing service and performance at scale. The system of the present disclosure uses a distributed blob storage for data records, wherein each tenant has their own partition within the blob storage. Blob storage is able to provide service and performance at scale. Blob storage alone, however, cannot solve the needs of a multi-tenant, cloud-based application in which customer inputs complex data queries to retrieve data records. The present disclosure describes a system that converts basic blob storage into a data store can manage complex data queries in an efficient and scalable way for multiple tenants.

Abstract: Systems and methods for forecasting future values of data streams are disclosed. One example method may include receiving information characterizing each of a plurality of forecasting models, retrieving historical data for each of a plurality of data streams, determining one or more constraints, dynamically selecting one of the plurality of forecasting models for each of the data streams based on accuracy metrics for the forecasting models, estimating cost metrics associated with each forecasting model, dynamically selecting the forecasting model based at least in part on the accuracy metrics, the cost metrics, and the determined constraints, and forecasting a first subsequent value of each data stream using the corresponding selected forecasting model.

Abstract: Techniques described herein provide automated generation of a narrated analytics playlist. Various implementations curate data from various data sources, where curating the data includes identifying attributes and relational data models. One or more implementations base the curating upon anecdotal data associated with a user. In response to receiving a trigger event to perform a query analysis, one or more implementations identify keywords to use in the query analysis, and extract information from the curated data based, at least in part on the one or more keywords. The extracted information is then analyzed to identify insights. In turn, one or more implementations generate a narrated analytics playlist using the insights. Some implementations utilize machine-learning algorithms to curate, extract and/or process data to generate insights. Various implementations abstract the data used to teach the machine-learning algorithms and share the abstracted data to other devices.

Abstract: Methods, systems, and devices for analyzing communication messages (e.g., emails or activities) to determine relationship strength using a distributed graph are described. In some systems, a user may be associated with a specific tenant. A database server of the system may receive communication messages associated with the user and a target user. The server may perform a natural language processing (NLP) analysis on the communication messages to extract metadata, and may generate or update a distributed graph indicating connections between users based on the extracted metadata. Using the connections of the graph, the server may calculate a closeness score between the user and the target user. Additionally, the server may calculate closeness scores between the target and other users associated with the tenant, and may determine the users with the greatest closeness scores. The server may send a suggestion for the determined users to initiate communication with the target.

Abstract: Provided are systems, methods, and media for handling dialogs based on user behavior data. An example method includes receiving an input paragraph having one or more factual sentences, in which each of the one or more factual sentences includes one or more words. Receiving an input question comprising one or more words. Performing word-level gaze prediction on the input paragraph to identify one or more predicted gaze attributes for the input paragraph. Extracting an answer to the input question based, at least in part, on the input paragraph, the input question, and the one or more predicted gaze attributes of the input paragraph. Transmitting the extracted answer.

Abstract: Improved entity identification is provided. Reference data sourced from various data sources may be used to more accurately identify an individual to improve the ability for multiple transaction processing systems to more effectively match identities for the transmission, receipt, and linking of data records. Accordingly, various enterprises are enabled to communicate about a particular entity without each enterprise having the same identifier or having the same, accurate entity demographic information.

Abstract: An artificial intelligence based method and apparatus for processing information. A specific embodiment of the method includes: acquiring a search record set within a preset time period; matching the search record set with an encyclopedia entry set, and selecting a first set of points of interest from the encyclopedia entry set according to a match result; matching the search record set with a microblog topic set, and selecting a second set of points of interest from the microblog topic set according to a match result; and adding the first set of points of interest and the second set of points of interest to a set of points of interest. This embodiment achieves an accurate acquisition of the points of interest, thus facilitating the implementation of a targeted information push.

Abstract: Some embodiments provide a method for quantifying the workload placed on a database by an application. The method identifies a first group of database queries that the application directed towards the database. The method produces a second group of queries by removing, from the first group of queries, queries that are duplicates based on the semantic structure of the queries. Based on a set of properties of the second group of queries, the method computes a complexity indicator that represents a complexity expression of the second group of queries.

Abstract: In optimizing net change data replication across a plurality of transactions in a replication environment, a source replication engine at a source database system: obtains a window in a source database log for the net change data replication; for a given row identifier found in the source database log, identifies an initial operation and a latest operation across the plurality of transactions within the window; compares the initial operation and the latest operation for the given row identifier to determine a net change to a row associated with the given row identifier; and stores the net change as a final operation on the given row identifier in an optimization repository for replication to a target database. The operations stored in the optimization repository are then sent to a target database system for replication to the target database.

Abstract: A mapping and query service for mapping between object-oriented programming objects and deep key-value data stores. The service to implement a store operation for a mapping and query service that supports the storage of a set of one or more objects having classes and fields written in source code of an object-oriented programming language in a deep key-value data store.

Abstract: In optimizing net change data replication across a plurality of transactions in a replication environment, a source replication engine at a source database system: obtains a window in a source database log for the net change data replication; for a given row identifier found in the source database log, identifies an initial operation and a latest operation across the plurality of transactions within the window; compares the initial operation and the latest operation for the given row identifier to determine a net change to a row associated with the given row identifier; and stores the net change as a final operation on the given row identifier in an optimization repository for replication to a target database. The operations stored in the optimization repository are then sent to a target database system for replication to the target database.