The present invention relates a method for high-performance traceability query oriented to multi-chain data association, comprising: identifying a target transaction needing the traceability query; searching out all corresponding target chains based on cross-chain transaction data association; making query requests parallelly; and executing the query among the target chains according to a key value of the target transaction and returning query results. The blockchain traceability query method proposed by the present invention is different from serialized block data query conducted in the chain-type structure, and the disclosed cross-chain query operation can be parallelly executed, leading to improved efficiency of traceability query. Opposite to the conventional blockchain where blocks are used as nodes of chains, the present invention directly uses sub blockchains as nodes of the SRB. Since sub blockchains can be dynamically added or removed, the present invention enhances the scalability of the entire system.

In one embodiment, a method includes receiving a user request to create a reminder from a client system associated with a user, wherein the user request does not specify an activation-condition for the reminder, determining one or more proactive activation-conditions for the reminder, storing the reminder in a reminder store, receiving one or more inputs associated with the user, determining a user context associated with the user based on the one or more inputs, determining the one or more proactive activation-conditions for the reminder are satisfied based on the user context, and sending instructions for presenting the reminder to the user to the client system responsive to determining the one or more proactive activation-conditions are satisfied.

Methods and apparatuses related to federated search of multiple sources with conflict resolution are disclosed. A method may comprise obtaining a set of data ontologies (e.g., types, properties, and links) associated with a plurality of heterogeneous data sources; receiving a selection of a graph comprising a plurality of graph nodes connected by one or more graph edges; and transforming the graph into one or more search queries across the plurality of heterogeneous data sources. A method may comprise obtaining a first data object as a result of executing a first search query across a plurality of heterogeneous data sources; resolving, based on one or more resolution rules, at least the first data object with a repository data object; deduplicating data associated with at least the first data object and the repository data object prior to storing the deduplicated data in a repository that has a particular data model.

An information processing system, method, and computer-readable medium that generate emotion values based on information related to interactions between one of a plurality of objects and other ones of the plurality of objects, the one of the plurality of objects being associated with a person, acquire at least one emotion value of the generated emotion values based on an identification of the person, and provide personal credit information of the person based on the acquired at least one emotional value.

A server system and methodology include the following operations. A request for tags associated with a resource is received from a tag widget associated with the resource. Responsive to the request, a tag weighting engine is executed that identifies the tags and determines, respectively, individual overall weighting factors for each of the tags. The tags and associated overall weighting factors are forwarded to the tag widget within the client. The individual overall weighting factors for a particular tag is based upon a combination of weighting factors including a context weight factor for the particular tag. The context weighting factor for the particular tag is based upon a past context for the particular tag specified by a past user and an active context in which a user of the tag widget is operating.

A method and apparatus for formulating a query by a digital assistant is provided herein. During operation a digital assistant will receive a query from a user. The query will have a type of device mentioned within the query. In response, the digital assistant will listen for any nearby device to announce itself. The query will then be modified by the digital assistant to include a device identification heard in the announcement. Results from the modified query will be provided to the user.

Methods to reduce agent effort and improve customer experience quality through artificial intelligence. The Agent Assist tool provides contact centers with an innovative tool designed to reduce agent effort, improve quality and reduce costs by minimizing search and data entry tasks The Agent Assist tool is natively built and fully unified within the agent interface while keeping all data internally protected from third-party sharing.

Automatically mapping and combining the application of machine learning models to answer queries according to semantic specification. A query is parsed to extract keywords from the query and to contextualize the query. Based on the keywords, machine learning models are selected that process concepts associated with the keywords. The machine learning models are sorted according to the contextualization of the query. The machine learning models are run on multimodal data according to a sorted order, where data resulting from an output of one of the machine learning models is used as input to another one of the machine learning models. A query result is output based on a result from running the machine learning models.

Methods, systems, and apparatuses for managing and selecting virtual warehouses for execution of queries on one or more data warehouses are described herein. A request to execute a query may be received. An execution plan, for the query, may be identified. A processing complexity for the query may be predicted based on the query and the execution plan. A plurality of virtual warehouses may be identified. An operating status and processing capabilities of the plurality of virtual warehouses may be determined. A subset of the plurality of virtual warehouses may be selected based on the processing complexity, the operating status of the plurality of virtual warehouses, and the processing capabilities of the plurality of virtual warehouses. The query may be executed on one of the subset of the plurality of virtual warehouses.

A method, apparatus and system for secure forensic investigation of a target machine by a client machine over a communications network. In one aspect the method comprises establishing secure communication with a server over a communications network, establishing secure communication with the target machine over the communications network, wherein establishing secure communication with the target machine includes establishing secure communication between the server and the target machine, installing a servelet on the target machine, transmitting a secure command to the servelet over the communications network, executing the secure command in the servelet, transmitting data, by the target machine, in response to a servelet instruction, and receiving the data from the target machine over the communication network.