International Business Machines Corporation

Faried Abrahams

Gandhi Sivakumar

Amol Ashok Dhondse

Anand Pikle

Kerard R Hogg

Lennox Epstein Thomas

Sarvesh S Patel

Kushal S Patel

Kerrie Lamont Holley

Vijayaganesh Subramanian

Kent R Ramchand

Sandeep R Patil

Sandeep Patil Ramesh

Craig M Trim

Raman Harishankar

Lalit Agarwalla

Piyush Sarwal

Maharaj Mukherjee

Riyazahamad Moulasab Shiraguppi

Ahamed Jalaldeen

Ali P Arsanjani

Siddharth N Purohit

Krishnan K Ramachandran

Sarbajit Kumar Rakshit

Sasikanth Eda

Kimberly Greene Starks

Vinod A Valecha

Geetha Adinarayan

Rashida A Hodge

Susan L Sylvia

Neal Fishman

Sivakumar Gandhi

Cristina Morariu

A method includes: creating, by a computing device, a virtual consolidation layer; replicating, by the computing device, snippets that are results of a query; copying, by the computing device, the replicated snippets to the virtual consolidation layer; performing, by the computing device and by a machine learning model, matching of particular ones of the snippets in the virtual consolidation layer; and producing, by the computing device, a search result comprising the matched snippets.

Data virtualization in natural language

Disclosed embodiments provide techniques for generating and using a Global Error-Code Sequence (GECS), with the role of generating, at request, a unique error identification number (ID). The scope of the unique identification number can include worldwide, company-wide, or a certain application ecosystem, such as eCommerce applications, etc. The GECS forms a strong correlation between an error condition and a known solution. While other logging signatures such as line numbers, stack traces, and addresses can change with new releases or invocations, the GECS enables a tighter coupling between an error condition and a knowledgebase document, which enables faster resolution of computer application problems and reduced downtime.

Globally unique error codes for knowledge document indexing in software systems

Selective compression of packet payload data in a 5G network includes receiving a congestion signal by user equipment (UE) connected to a broadband cellular network based on network traffic congestion in hardware of the network and indicating the network traffic congestion, determining current processor utilization of the UE, based on the received congestion signal, the determined current processor utilization, and known times for data compression and decompression, determining whether to automatically enable selective packet payload data compression on the UE, and based on determining to automatically enable selective packet payload data compression, compressing payload data of data packet(s) generated by the UE, and forwarding the data packet(s) with the compressed payload data for transmission on the broadband cellular network.

Selective compression of packet payload data in a 5G network

A computer-implemented method for selectively excluding data from compression prior to uplink to a telecommunication system. In an embodiment, the method analyzing a request by an application, executing within a device, to wirelessly uplink data to a telecommunication node. The method further includes establishing a set of logical channels assigned to the application. The method further includes transferring the data among one or more logical channels, of the set of logical channels, based on a status flag related to data compression corresponding to the data. The method further includes determining that the data is transferred via a compression-disabled logical channel, of the set of logical channels. The method further includes responding to determining that the data is transferred via the compression-disabled logical channel by bypassing a data compression function prior to preparing the data for uplink. The method further includes uplinking the data to the telecommunication node.

Selective compression of data for uplink to a telecommunication network

In an approach, a processor identifies that a vehicle has been exposed to a first user, the first user associated with an infectious disease. A processor monitors, via a wireless ad hoc network, presence of a mobile device at a location of the vehicle. A processor identifies the presence of the mobile device at the location of the vehicle. A processor sends a notification to the mobile device, the notification specifying that the vehicle has been exposed to the infectious disease.

Vehicle contamination notification using ad hoc networks

A computer-implemented method is used for each of two or cameras on a device, where a first camera of the two or cameras is located under a display of the device. The method further includes defining, for each camera, a best effect region on the display including a first best effect region for the first camera. The method also includes identifying, for each of one or more feeds, a feed display area including a first feed display area, where each feed display location uses a portion of the display. The method includes activating the first camera for a first feed, wherein the first feed has a first feed display area that overlaps the first best effect region.

Dynamic activation of under-display camera

A system and method for intelligent classification for product pedigree identification are presented. A transactional block may be dynamically created for recording both pedigree information for one or more supply ingredients at a time of origin and one or more parameters relating to the one or more supply ingredients at each temporal event. One or more transactional blocks may be linked via a shared ledger according to the one or more supply ingredients and the one or more parameters.

Intelligent classification for product pedigree identification

An approach includes a system implemented in a computer infrastructure including a processor. The approach further includes the processor configured to receive dimensionally aware linkages. The approach further includes the processor configured to retrieve aggregated data from a data set. The approach further includes the processor configured to identify at least one affinity cluster related to the dimensionally aware linkages in at least two dimensions and the retrieved aggregated data by performing at least one lookup linkage which matches at least one dimension of the at least two dimensions of the dimensionally aware linkages with the retrieved aggregated data. The approach further includes the processor configured to provide personalized content to a user having same or similar user preferences as the received dimensionally aware linkages based on the identified at least one affinity cluster.

Personalized content and services based on profile information

An approach is provided in which a cognitive system engages in a conversation that includes multiple participants. The cognitive system detects a diversion indicator during the conversation that is a trigger to the cognitive system perform a diversion action. The cognitive system identifies the diversion action that corresponds to the diversion indicator and performs the diversion action during the conversation accordingly.

Controlling external behavior of cognitive systems

A mapping is constructed between a node of a cultural hierarchy and a node of an organizational hierarchy. The cultural hierarchy is a data structure representing an arrangement of characteristics of different social levels relative to one another in a culture. The organizational hierarchy is a data structure representing an arrangement of characteristics of different roles of people relative to one another in a group. A set of cultural attributes is constructed to represent a persona of a human user according to mapping. Using a cultural attribute, an adjustment rule is selected from a library. A machine output is modified according to the adjustment rule. The machine output is in response to a dialog between a data processing system and human user in a machine-human interaction. The adjusted output is transformed and presented as a response to the human user in the machine-human interaction.

Culturally-aware cognitive system for human interactions

Approaches presented herein enable automatically fulfilling an obligation under a smart contract. A block is added to a blockchain ledger in response to an event that triggers the obligation. The block includes data related to the event. Inferences related to the event are derived based on an analysis of event data and historical data incorporated in prior blocks in the blockchain ledger. Based on the inferences, a potential cause of the event is derived. Based on the potential cause, an interested stakeholder to the fulfilling of the obligation is identified. The interested stakeholder is added to a group that is allowed access to the blockchain ledger corresponding to the smart contract.

Granting access to a blockchain ledger

Multi-turn conversation systems that are personalized to a user based on insights derived from big data are described. A computer-based conversation system for interacting with a user includes: a CPU, a computer readable memory, and a computer readable storage medium associated with a computer device; and program instructions defining a statement and question framer that is configured to: obtain insights about a user from a big data engine; and generate a response to an input from the user based on the insights and the input. The program instructions are stored on the computer readable storage medium for execution by the CPU via the computer readable memory.

Dynamic personalized multi-turn interaction of cognitive models

Multi-turn conversation systems that are personalized to a user based on insights derived from big data are described. A method includes: receiving, by a computer device, input from a user; obtaining, by the computer device, insights about the user; generating, by the computer device, a response based on the insights and the input; and outputting, by the computer device, the response.

A method and associated system for generating a service specification of a solution. Each process of at least one process is decomposed into at least one atomic service process. The service specification of the solution to be compatible with both a process model framework that includes the at least one process and a data model framework that includes at least one data element that is indirectly matched to the at least one process. The service specification represents a respective process interface of each atomic service process that performs a respective atomic service in the solution. The customized service specification is stored in a database.

Generation of service specification of a solution

Prepending a name object or setting a type of a software object to a name and prepending a value object to the software object provides inheritance of a name value pattern by the software object to establish particular types or classes of attributes of the software object without modification of the software object itself that is thus strongly typed and accessible by type.

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Laytonsville, MD, United States of America

Faried Abrahams