Abstract: Attribute-based application programming interface (API) comparative benchmarking is provided. In response to determining that a target API maps to an existing API classification based on attributes of the target API, a weighted average of benchmark confidence scores of other APIs in a same class as the target API is determined. A benchmark confidence score is determined for the target API based on feedback, reviews, and ratings. The benchmark confidence score of the target API is compared with the weighted average of benchmark scores. An attribute-based API classification mapping is updated based on the comparison. Pricing for the target API is determined based on a weighted average of API pricing across the other APIs in the same class as the target API.

Abstract: Approaches presented herein enable optimizing resource allocation to a bid request response based on a cognitive analysis of natural language artifacts. More specifically, a bid request and a plurality of supporting artifacts in a natural language are obtained. A cognitive analysis of the request and supporting artifacts is performed to extract a set of information entities. The extracted information entities are normalized using a lexical-relations based graph database to classify the set of extracted information entities as standardized concepts. A subset of the set of the standardized concepts is identified as a set of parameters corresponding to a set of predetermined variables. Each variable of the set of predetermined variables is weighted according to a likelihood that the variable indicates a relevance of a resource. A probability that a particular resource is relevant is determined based on the weighting and that resource is assigned to the bid request response.

Abstract: 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.

Abstract: A method, system and computer program product for determining API pricing. Consumption parameters are identified using a supervised learning model. The API consumption parameters refer to any parameters that can be used to describe an API (functionality or otherwise) and can be used to compare other comparable APIs in similar domains provided by other providers. Furthermore, reference pricing is determined using machine learning using the identified API consumption parameters. Additionally, the API price is determined dynamically using the identified API consumption parameters and the determined reference pricing. An API pricing score is then derived for the API price using the supervised learning model. The API price is selected as the suggested price for the API in response to the API pricing score exceeding a threshold value. In this manner, an API price is established that reflects the true value of the API assessed by the API consumer.

Abstract: 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.

Abstract: A method, system and computer program product for determining API pricing. Consumption parameters are identified using a supervised learning model. The API consumption parameters refer to any parameters that can be used to describe an API (functionality or otherwise) and can be used to compare other comparable APIs in similar domains provided by other providers. Furthermore, reference pricing is determined using machine learning using the identified API consumption parameters. Additionally, the API price is determined dynamically using the identified API consumption parameters and the determined reference pricing. An API pricing score is then derived for the API price using the supervised learning model. The API price is selected as the suggested price for the API in response to the API pricing score exceeding a threshold value. In this manner, an API price is established that reflects the true value of the API assessed by the API consumer.

Abstract: Embodiments for utilizing a human compound eye using internet of things (“HCEI”) for obstacle protection of a user by a processor. One or more objects may be determined within an obstacle threshold distance in relation to a user according to data captured from one or more internet of things (IoT) devices associated with a wound dressing, a mobility assistance device, or a combination thereof. The user may be alerted of the one or more objects within the obstacle threshold distance.

Abstract: 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.

Abstract: Approaches presented herein enable managing an incoming communication on a communication device from a communication channel. Specifically, the incoming communication is received and analyzed to determine, based on a context of the incoming communication, a situational pattern from among a plurality of situational pattern models. Based on the determined situational pattern, a criticality level is identified. One or more prompts from among a plurality of prompts are transmitted to a wearable device based on the criticality level for display to provide notification to a user of the criticality of the incoming communication.

Abstract: Embodiments for utilizing a human compound eye using internet of things (“HCEI”) for obstacle protection of a user by a processor. One or more objects may be determined within an obstacle threshold distance in relation to a user according to data captured from one or more internet of things (IoT) devices associated with a wound dressing, a mobility assistance device, or a combination thereof. The user may be alerted of the one or more objects within the obstacle threshold distance.

Abstract: A method and associated systems for a multidimensional information repository for managing dynamic time-sensitive and space-sensitive user profiles. A profile-management system receives an incoming event that identifies a user profile and is associated with a location, a time period, and a subject. The system searches the repository for records that identify the profile, location, time period, and subject and creates any such records that do not already exist. The system then creates time-sensitive and space-sensitive linkages that link the user profile record to the location, time-period, and subject records. The system dynamically updates these linkages in response to changes to the user profile and uses the linkages to assign context to queries submitted to a main database. In another embodiment, the system recommends additional linkages based on patterns identified in the newly created linkages.

Abstract: A security control system for a kinematic robot uses a cognitive assessment agent to map proposed instructions to either legitimate or illegitimate actions based on contextual variables. The agent computes a security anomaly index score representing a variance of a likely kinematic action of the robot compared to acceptable actions. If the score exceeds a predetermined threshold, a security alert is generated for the robot's administrator. The contextual variables include a user profile, a user location, and subject matter of the kinematic actions. The analysis compares input text to predefined classification metadata, and can also compare verbal phrases or body gestures to corresponding baselines. Different numeric weights can be applied to the contextual variables. The computing begins with a default value for the score and thereafter increments or decrements the score based on the weights. The weights can be adjusted based on a supervisory appraisal of the computed score.

Abstract: A security control system for a kinematic robot uses a cognitive assessment agent to map proposed instructions to either legitimate or illegitimate actions based on contextual variables. The agent computes a security anomaly index score representing a variance of a likely kinematic action of the robot compared to acceptable actions. If the score exceeds a predetermined threshold, a security alert is generated for the robot's administrator. The contextual variables include a user profile, a user location, and subject matter of the kinematic actions. The analysis compares input text to predefined classification metadata, and can also compare verbal phrases or body gestures to corresponding baselines. Different numeric weights can be applied to the contextual variables. The computing begins with a default value for the score and thereafter increments or decrements the score based on the weights. The weights can be adjusted based on a supervisory appraisal of the computed score.

Abstract: 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.

Abstract: Embodiments include method, systems and computer program products for proximity based content security. Aspects include receiving a request to access a secured data by a user device; accessing, by a processor, a security profile for the secured data; obtaining environmental data from one or more sensors related to the user device, wherein a type of the one or more sensors is determined by the security profile; and providing access to the secured data based upon a determination that the environmental data is in compliance with the security profile.

Abstract: A computing system for predictive traffic management using virtual lanes. In an embodiment, the system dynamically monitors and collects traffic conditions in real time, performs analytics on the collected traffic data, utilizes a neural network or other self-learning computer to assist in predictive traffic modeling, and interfaces with a public transfer system to provide an allocation/reallocation of lanes available for traffic use to optimize traffic flow and/or control traffic signals, and can provide vehicles (human driver or driverless/self-driving) with real time optimal route guidance, including use of alternate routes and a holographic image that shows and may also provide audio indications of lane allocation.

Abstract: A model-based approach for transforming data. A modeling framework that includes a plurality of rules for performing transformations of data is developed. A data unit is configured. The data unit is assigned to a job that includes one or more rules of the plurality of rules. The job transforms the data unit from a data format of a source system into a data format of a destination system. Usage statistics for at least one rule of the job are monitored. An aggregate rule is determined based on a first atomic rule and a second atomic rule. The first atomic rule and the second atomic rule are identified by at least one, or in part by a common pattern. A first rule of the job is identified based on the usage statistics of a plurality of data units. The first rule is removed from memory.

Abstract: The factual accuracy of an event is verified. Event data is received by a computer, whereby the event data includes actor data related to at least one actor involved in the event and location data related to a location of the event. A factual scenario is created based on the event data. A cognitive reasoning and analysis of the event data is performed to derive inferences regarding the event and a time-sequenced series of inferences is composed based on the cognitive reasoning and analysis of the event data. Integrity of the event data is validated by comparing a data points from different sources and at least one flag is prompted when an instance of factual inconsistency is identified by the step of validating the integrity. A rendering of the event is generated based on the factual scenario and the time-sequenced series of inferences.

Abstract: 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.

Abstract: Approaches presented herein enable managing an incoming communication on a communication device from a communication channel. Specifically, the incoming communication is received and analyzed to determine, based on a context of the incoming communication, a situational pattern from among a plurality of situational pattern models. Based on the determined situational pattern, a criticality level is identified. One or more prompts from among a plurality of prompts are transmitted to a wearable device based on the criticality level for display to provide notification to a user of the criticality of the incoming communication.