Abstract: In some examples, a user, either a customer or potential customer of a business, engages in conversations with a virtual assistant (VA) provided by the business. The virtual assistant (VA) is further supported by one or more human assistants (HA), if needed. In embodiments, to facilitate seamless transitions between a VA and a HA, when needed, an intelligent decision maker (IDM) is provided. The IDM receives a user question and a proposed answer to the question from a VA, evaluates the proposed answer in the context of the conversation, and determines if the proposed answer requires further review by an HA. In response to a determination that the proposed answer requires further review, the IDM sends the proposed answer to an HA, and, in response to an indication by the HA, takes further action in the conversation.

Abstract: Techniques for secure electronic collaboration among parties to provide dynamic cyber insurance are disclosed. A profile describing information technology (IT) infrastructure for an entity is retrieved from an electronic distributed ledger. At least a portion of the profile is provided to a risk evaluator using the electronic distributed ledger. A cyber security risk evaluation associated with the profile is retrieved from the electronic distributed ledger. A request for cyber insurance from the entity is received. Cyber insurance parameters for the entity are determined automatically, using a computer processor, and based on the cyber security risk evaluation. The entity acquires cyber insurance based on the determined cyber insurance parameters.

Abstract: Methods, systems, and computer program products for content marshaling using biometric data are provided herein. A computer-implemented method includes estimating a cognitive state of a user based at least in part on analyzing one or more sets of biometric data pertaining to the user; dynamically compiling multi-modal content for the user based at least in part on (i) the estimated cognitive state of the user, (ii) one or more user parameters, and (iii) content availability information; and outputting the compiled content to the user via one or more devices.

Abstract: An example operation includes one or more of identifying, by an archiving server node, a unique archival policy for each of a plurality of blockchain nodes, executing, by the archiving server node, a consensus mechanism to determine at least one block from a plurality of blocks of the plurality of the blockchain nodes to be archived, and running the unique archival policy to archive the at least one block from the plurality of the blocks.

Abstract: Techniques for secure electronic collaboration among parties to provide dynamic cyber insurance are disclosed. A profile describing information technology (IT) infrastructure for an entity is retrieved from an electronic distributed ledger. At least a portion of the profile is provided to a risk evaluator using the electronic distributed ledger. A cyber security risk evaluation associated with the profile is retrieved from the electronic distributed ledger. A request for cyber insurance from the entity is received. Cyber insurance parameters for the entity are determined automatically, using a computer processor, and based on the cyber security risk evaluation. The entity acquires cyber insurance based on the determined cyber insurance parameters.

Abstract: In some examples, a user, either a customer or potential customer of a business, engages in conversations with a virtual assistant (VA) provided by the business. The virtual assistant (VA) is further supported by one or more human assistants (HA), if needed. In embodiments, to facilitate seamless transitions between a VA and a HA, when needed, an intelligent decision maker (IDM) is provided. The IDM receives a user question and a proposed answer to the question from a VA, evaluates the proposed answer in the context of the conversation, and determines if the proposed answer requires further review by an HA. In response to a determination that the proposed answer requires further review, the IDM sends the proposed answer to an HA, and, in response to an indication by the HA, takes further action in the conversation.

Abstract: A computer-implemented method includes detecting, using a processor system, a first delay in a conversation system. Initial contextual data is received at a first orchestration layer of the processor system, where the initial contextual data describes a context of a user. The first orchestration layer queries a first data source, based on the initial contextual data. Based on querying the first data source, the first orchestration layer augments the initial contextual data to determine updated contextual data describing the context of the user. Filler content personalized to the user is generated based on the updated contextual data describing the context of the user. The filler content is presented through a user interface during the first delay, responsive to detecting the first delay in the conversation system.

Abstract: Methods and arrangements for determining at least one employment trait of an individual from online activity. Collecting a plurality of employment task data points from a plurality of online sources, wherein each employment task comprises a data set indicative of a path taken by at least one individual from a starting point to an ending point, wherein the starting point and ending point are defined on the basis of common parameters. The collected plurality of employment task data points are assessed, to determine an employment trend of the individual and creating at least one profile of the individual based on the determined employment trend. At least one profile is stored at a data storage location. Other variants and embodiments are broadly contemplated herein.

Abstract: A caching method, system, and computer program product include compiling a combined action of a social interaction with a sharing of an object via a Uniform Resource Locator (URL) in real-time and from an offline database, extracting semantic information from the combined action, describing the semantic information of the combined action as an embedding of the object in a general object vector space, and creating a caching policy for access to the object based on a prediction of an access time derived from the general object vector space and the description of the combined action.

Abstract: Methods, systems, and computer program products for content marshaling using biometric data are provided herein. A computer-implemented method includes estimating a cognitive state of a user based at least in part on analyzing one or more sets of biometric data pertaining to the user; dynamically compiling multi-modal content for the user based at least in part on (i) the estimated cognitive state of the user, (ii) one or more user parameters, and (iii) content availability information; and outputting the compiled content to the user via one or more devices.

Abstract: A computer-implemented method includes detecting, using a processor system, a first delay in a conversation system. Initial contextual data is received at a first orchestration layer of the processor system, where the initial contextual data describes a context of a user. The first orchestration layer queries a first data source, based on the initial contextual data. Based on querying the first data source, the first orchestration layer augments the initial contextual data to determine updated contextual data describing the context of the user. Filler content personalized to the user is generated based on the updated contextual data describing the context of the user. The filler content is presented through a user interface during the first delay, responsive to detecting the first delay in the conversation system.

Abstract: A caching method, system, and computer program product include compiling a combined action of a social interaction with a sharing of an object via a Uniform Resource Locator (URL) in real-time and from an offline database, extracting semantic information from the combined action, describing the semantic information of the combined action as an embedding of the object in a general object vector space, and creating a caching policy for access to the object based on a prediction of an access time derived from the general object vector space and the description of the combined action.

Abstract: Methods and arrangements for identifying burden comprehension in multimedia content. A contemplated method includes: accepting multimedia input; detecting components of the multimedia input; determining a comprehension burden score of each of the detected components; and thereupon calculating a total comprehension burden score for the multimedia input. Other variants and embodiments are broadly contemplated herein.

Abstract: Methods and arrangements for generating a learning graph. A contemplated method includes: utilizing at least one processor to execute instructions to perform the steps of: receiving a proficiency input relating to a student; receiving a target knowledge node, wherein the target knowledge node represents at least one skill the student does not currently possess; determining at least one skill requirement of the at least one skill; identifying at least one path between the proficiency input and the target knowledge node based upon the at least one determined skill requirement; calculating a gap between the proficiency input and the target knowledge node at the at least one identified path; and recommending at least one learning content module based upon the calculated gap.

Abstract: Method and apparatus for generating a knowledge graph. A first electronic document is received and each of a plurality of portions of the first electronic document is categorized as one of i) an introduction section and ii) a theory section, according to a rhetorical structure theory (“RST”) scheme. A first glossary of terms for the first document is determined. The knowledge graph containing a first plurality of nodes is generated, where each of the first plurality of nodes corresponds to a respective term from the first glossary of terms, and where a first edge between a first node corresponding to a first term and a second node corresponding to a second term is created based on determining that the first term appears within at least one introduction section and that the first term and the second term appears together within at least one theory section.

Abstract: Methods and arrangements for discovering entity types for a set of records. A set of records is input, with each record comprising attributes with associated attribute values. The records are grouped into candidate entity types in view of at least one of: the attribute values of the records, at least one domain ontology and at least one dimension hierarchy. An interestingness measure of each candidate entity type is calculated, via estimating interestingness based on at least one factor selected from the group consisting of: a correlation between attribute values of records, a number of attributes, a log of queries issued to a server, and an average group size for candidate entity types. At least one candidate entity type is validated based on the calculated interestingness measures. Other variants and embodiments are broadly contemplated herein.

Abstract: Systems and associated methods for address standardization and applications related thereto are described. Embodiments exploit a common context in a taxonomy and a given address to detect and correct deviations in the address. Embodiments establish a possible path from a root of the taxonomy to a leaf in the taxonomy that can possibly generate a given address. Given a new address, embodiments use complete addresses, and/or segments or elements thereof, to compute the representations of the elements and find a closest matching leaf in the taxonomy. Embodiments then traverse the path to a root node to detect the agreement and disagreement between the path and the address entry. Taxonomical structured is thus used to detect, segregate and standardize the expected fields.

Abstract: Methods and arrangements for determining at least one employment trait of an individual from online activity. Collecting a plurality of employment task data points from a plurality of online sources, wherein each employment task comprises a data set indicative of a path taken by at least one individual from a starting point to an ending point, wherein the starting point and ending point are defined on the basis of common parameters. The collected plurality of employment task data points are assessed, to determine an employment trend of the individual and creating at least one profile of the individual based on the determined employment trend. At least one profile is stored at a data storage location. Other variants and embodiments are broadly contemplated herein.

Abstract: In the context of data administration in enterprises, an effective manner of providing a central data warehouse, particularly via employing a tool that helps by analyzing existing data and reports from different business units. In accordance with at least one embodiment of the invention, such a tool analyzes the data model of an enterprise and proposes alternatives for building a new data warehouse. The tool, in accordance with at least one embodiment of the invention, models the problem of identifying fact/dimension attributes of a warehouse model as a graph cut on a Dependency Analysis Graph (DAG). The DAG is built using existing data models and the report generation scripts. The tool also uses the DAG for generation of ETL (Extract, Transform Load) scripts that can be used to populate the newly proposed data warehouse from data present in the existing schemas.

Abstract: Methods and arrangements for generating a learning graph. A contemplated method includes: utilizing at least one processor to execute instructions to perform the steps of: receiving a proficiency input relating to a student; receiving a target knowledge node, wherein the target knowledge node represents at least one skill the student does not currently possess; determining at least one skill requirement of the at least one skill; identifying at least one path between the proficiency input and the target knowledge node based upon the at least one determined skill requirement; calculating a gap between the proficiency input and the target knowledge node at the at least one identified path; and recommending at least one learning content module based upon the calculated gap.