Abstract: A computer-implemented method is provided for processing a set D of conversation logs. The method includes learning, by a processor device, a set R of entity relation mining rules from a set K of known entity utterances uttered by known entities. The method further includes automatically recommending, by the processor device, extended utterances of the known entities from unrecognized ones of the known entities based on the set R.

Abstract: The present disclosure provides a method, computer system and computer program product facilitating generation of a conversation content. A computer-implemented method comprises: obtaining, by a device operatively coupled to one or more processors, history conversation data of an user; determining, by the device, a professional level of the user based on the history conversation data; and generating, by the device, a conversation content for the user based on the professional level of the user.

Abstract: A cognitive conversation system that generates effective diagnostic questions is provided. The cognitive conversation system receives a set of currently known symptoms (or currently available answers to diagnostic questions) of a reported problem or fault. The system identifies (i) a set of possible root causes of the reported problem based on the currently known symptoms and (ii) probabilities for the set of possible root causes by using a bipartite graph data structure that links possible symptoms with possible root causes. Upon determining that at least one possible root cause has a probability that is higher than a threshold, the system presents an explanation or solution associated with the at least one possible root cause. Upon determining that none of the possible root causes in the set of possible root causes has a probability higher than the threshold, the system presents a question based on information entropy that is computed based on probabilities of the identified possible root causes.

Abstract: A computer-implemented method is presented for enabling hierarchical conversational policy learning for sales strategy planning. The method includes enabling a user to have a conversation with a robot via a conversation platform, employing a plan database to store general plans used in the conversation, employing an industry database to store a plurality of candidate plans pertaining to sales promotions, and employing a plan and policy optimizer to allow the robot to select and output an optimal plan from the plurality of candidate plans, the optimal plan determined by hierarchical reinforcement learning via a first learner and a second learner, the first leaner selecting the optimal plan and the second learner selecting an optimal action.

Abstract: Computer-implemented method for searching for information related to an incident generated in a server system, a system and a computer program product. The method includes extracting context information from a current ticket describing the incident, the context information including a first expression describing a symptom of the incident and indicating at least one component of the server system associated with the symptom; determining a data source which generates data in which the information related to the incident is to be searched for at least according to the at least one component; and using the first expression describing the symptom and a second different expression describing the symptom as keywords to search for the information related to the incident in the data.

Abstract: A method for managing a vehicle brake system includes collecting sensor data from one or more sensors in or around the vehicle, calculating brake effectiveness values based on the sensor data, calibrating the brake effectiveness values based on environmental context data associated with the vehicle, accumulating the calibrated brake effectiveness values as a dataset, generating a prediction curve or formula based the dataset, and scheduling a maintenance alarm for the brake system based on the brake effectiveness values.

Abstract: A computer-implemented method is provided for medical conversation generation. The method includes receiving, by a processor device, clinical findings for a patient. The method further includes calculating, by the processor device based on the clinical findings, (i) a suspected disease and (ii) symptoms for inquiry with (iii) a symptom significance for each of the symptoms. The method also includes decomposing, by the processor device, the symptoms from a multi-dimensional abstraction. The method additionally includes selecting, by the processor device, an inquiry strategy based on the symptom significance calculated for each of the symptoms. The method further includes calculating, by the processor device based on a decomposition of the symptoms and the inquiry strategy, a combination benefit/cost and evaluating the combination benefit/cost to provide an optimized combination result.

Abstract: A vehicle occupant comfort system, comprises a processor that stores computer executable components stored in memory. A plurality of sensors sense ambient conditions associated with exterior and interior conditions of a vehicle. A context component infers or determines context of an occupant of the vehicle. A comfort model component implicitly and explicitly trained on occupant comfort related data analyzes information from the plurality of sensors and context component. A comfort controller adjusts environmental conditions of a passenger compartment of the vehicle based at least in part on output of the comfort model component.

Abstract: Methods and systems for treating a disease include navigating a symptom-centric decision tree which accounts for probabilities for symptoms and diseases and emergency values for the symptoms and diseases, based on information provided by a user, to determine a disease. A treatment is provided to the user based on the determined disease.

Abstract: A computer-implemented method, computer program product, and computer processing system are provided for generating inferences from a forest of predefined problem determination trees using a processor-based conversation platform. The method includes selecting a tree from among the forest of predefined problem determination trees, responsive to user utterances uttered during an inference generating session. The method further includes navigating the tree to allocate a relevant tree node to generate a problem diagnosis question or a problem resolution action by understanding the user utterances among common interaction patterns in problem diagnosis and problem resolution dialogs. The method also includes providing speech for uttering the problem diagnosis question or the problem resolution action to a user.

Abstract: In an approach for eliciting user demands for item recommendation, one or more computer processors retrieve one or more items based on a user demand. The one or more computer processors update the one or more items based on the user demand. The one or more computer processors extract the one or more representative words corresponding to the one or more items. The one or more computer processors build a candidate item list based on the one or more representative words. The one or more computer processors generate one or more eliciting questions to help a user select an item based on the candidate item list.

Abstract: A computer-implemented authentication method, the method comprising: matching a brain pattern sequence with a predetermined password to allow access to a system, wherein the brain pattern sequence is calculated by analyzing a signal slope of a slope threshold of the brain activity to determine a timing and a duration of the brain activity.

Abstract: An authentication method, system, and computer program product for decoding brain activity into a brain pattern sequence, applying brain dialog to interact with a user while the user is entering the brain pattern sequence, and matching the brain pattern sequence with a predetermined password to allow access to a system.

Abstract: A measurement device and method for focusing and leveling are disclosed. The device includes a measuring optical path and a first monitoring optical path. Measuring light in the measuring optical path interacts with a wafer and is then incident on a measuring detector to form thereon a measuring mark. First monitoring light in the first monitoring optical path is incident on a measuring detector to form thereon a first monitoring mark. An error in a measurement result of the wafer that arises from a drift of the measuring detector can be eliminated by compensating for a vertical deviation of the wafer obtained by subtracting a drift of the first monitoring mark from a displacement of the measuring mark. In this way, measurement accuracy and stability can be improved by monitoring and correcting the drift of the measuring detector.

Abstract: Managing a brake system of a vehicle includes collecting sensor data from one or more sensors in or around the vehicle, calculating brake effectiveness values based on the sensor data, calibrating the brake effectiveness values based on environmental context data associated with the vehicle, accumulating the calibrated brake effectiveness values as a dataset, generating a prediction curve or formula based the dataset, and scheduling a maintenance alarm for the brake system based on the brake effectiveness values.

Abstract: The present disclosure relates to identifying an origin/destination pair. Aspects include identifying an origin/destination pair in a service, which includes determining a current time when the current operation is executed in response to failure of a current operation for recording an origin/destination pair. Aspects also include determining a previous time when a last operation was executed for recording an origin/destination pair and identifying a missing point causing failure of the current operation based on a time interval between the current time and the previous time.

Abstract: The present disclosure relates to identifying an origin/destination pair. Aspects include identifying an origin/destination pair in a service, which includes determining a current time when the current operation is executed in response to failure of a current operation for recording an origin/destination pair. Aspects also include determining a previous time when a last operation was executed for recording an origin/destination pair and identifying a missing point causing failure of the current operation based on a time interval between the current time and the previous time.

Abstract: Systems and methods for facilitating an automatic adjustment of a braking system is provided. In one example, a computer-implemented method can comprise generating, by a system operatively coupled to a processor, a braking curve model based on braking usage pattern data corresponding to one or more vehicles. The computer-implemented method can also comprise adjusting, by the system, a supplemental braking component of the first vehicle based on a simulation of one or more braking components corresponding to the one or more vehicles, wherein the one or more braking components is represented by the braking curve model.

Abstract: Systems and methods for facilitating an automatic adjustment of a braking system is provided. In one example, a computer-implemented method can comprise generating, by a system operatively coupled to a processor, a braking curve model based on braking usage pattern data corresponding to one or more vehicles. The computer-implemented method can also comprise adjusting, by the system, a supplemental braking component of the first vehicle based on a simulation of one or more braking components corresponding to the one or more vehicles, wherein the one or more braking components is represented by the braking curve model.

Abstract: A cognitive conversation system that generates effective diagnostic questions is provided. The cognitive conversation system receives a set of currently known symptoms (or currently available answers to diagnostic questions) of a reported problem or fault. The system identifies (i) a set of possible root causes of the reported problem based on the currently known symptoms and (ii) probabilities for the set of possible root causes by using a bipartite graph data structure that links possible symptoms with possible root causes. Upon determining that at least one possible root cause has a probability that is higher than a threshold, the system presents an explanation or solution associated with the at least one possible root cause. Upon determining that none of the possible root causes in the set of possible root causes has a probability higher than the threshold, the system presents a question based on information entropy that is computed based on probabilities of the identified possible root causes.