International Business Machines Corporation

Norbert Herman

Shubhadip Ray

Karl J Cama

Daniel T Lambert

Gregory J Boss

Andrew Ronald Freed

Dhandapani Shanmugam

Siddique M Adoni

Avik Sanyal

Andrew S Christiansen

Mudhakar Srivatsa

Raghu Kiran Ganti

Sarbajit Kumar Rakshit

Craig M Trim

Rama Kalyani T Akkiraju

Philip A Westcott

Disclosed embodiments provide techniques for automated technical support based on cognitive capabilities and preferences of a user. A user profile is obtained which includes a skill level assessment. A solution path includes one or more potential solutions for a problem. One or more solutions in the solution path are presented to a user as a potential remedy for a technical problem, based on the cognitive capabilities and preferences of a user.

Cognitive computer diagnostics and problem resolution

Using an analytical model, a problem related to a product is identified from a collection of report data, the product being a three dimensional (3D) solid having a shape and produced from a manufacturing process. The problem is correlated with a set of factors. The set of factors describes a circumstance in which a user performs an operation of the product. According to a weight assigned to the problem, the problem is selected for prototyping. Using a processor and a memory, the set of factors and the operation are simulated by using a modified design of the product. In response to the modified design solving the problem, a specification of the modified design is provided for 3D printing to the user.

Automated prototype creation based on analytics and 3D printing

Embodiments herein provide data clustering and user modeling for next-best-action decisions. Specifically, a modeling tool is configured to: receive indicators within unstructured social data from a plurality of users; analyze the unstructured social data of each of the plurality of users to assign a set of feature vectors to each of the plurality of users, each feature vector corresponding to one or more personality characteristics of each of the plurality of users; and analyze the feature vectors to identify two or more users from the plurality of users sharing a set of similar feature vectors. The modeling tool is further configured to: group the two or more users from the plurality of users sharing the set of similar feature vectors to form a cluster; identify attributes of the cluster; and input the attributes of the cluster into a predictive model to determine an offer corresponding to the cluster.

Data clustering and user modeling for next-best-action decisions

Methods, computer program products, and systems are presented. The methods include, for instance: determining user clusters and navigation-type clusters based on multiple information requests, and training facets and corresponding usefulness factor of the facets from the multiple information requests by machine learning. When a user submits a query, the user and the query is respectively mapped with one of the user clusters and the navigation-type clusters, and the query is customized based on the associated pair of clusters. Results of the query are obtained, ranked by usefulness of the facets as determined according to the pair of clusters, and presented to the user.

Dynamic faceting for personalized search and discovery

Generating insight on a set of data is provided. A request for information regarding a specific topic is received from a client device corresponding to a requester. An analysis is performed on the request and a type of the information requested is determined based on the analysis. A set of information vendors is selected from a plurality of known information vendors based on the type of the information requested and other factors. Insights on the type of the information requested are obtained from the selected set of information vendors and an analysis is performed on the insights. A response to the request is generated based on the analysis of the insights on the type of the information requested that was obtained from the selected set of information vendors. The response to the request is sent to the client device corresponding to the requester.

Data analytics and insights brokerage service

A method and system are provided for next location prediction. The method includes inferring, by a hardware processor, a store layout, based on user location data and user transaction data for a plurality of users. The method further includes clustering, by the hardware processor, the plurality of users based on the user transaction data to form a set of clusters. The method also includes ensembling, by the hardware processor, users within each of the clusters and building a location prediction model for each of the clusters. The method additionally includes predicting, by the hardware processor, a next location of a particular user from the plurality of users based on a weighted vote taken over the location prediction model for the cluster corresponding to the particular user. The cluster corresponding to the particular user includes at least one other user from the plurality of users in addition to the particular user.

Next location prediction

A method and system for improving wearable device function control is provided. The method includes detecting a first gesture executed by a user. A speed and direction of the first gesture; an eye focus of the user, and a time period associated with eye focus being directed towards a display portion of a wearable device are detected. The first gesture is analyzed with respect to previously determined mapping data, the speed and direction of the first gesture, the eye focus of the user, and the time period. In response, a specified function of the wearable device associated with the first gesture is determined and executed.

Wearable device control

A vehicle accident detection method and system is provided. The method includes receiving location coordinates associated with a location of an occurring vehicular accident. Data associated with possible causes of the vehicular accident is received from sensors. Traffic related rules associated with a geographical location are retrieved and analyzed with respect to the data. Parameters associated with at least one vehicle involved in the vehicular accident and a possible cause are determined via execution of programming logic and transmitted to additional systems. The possible cause for the vehicular accident is determined from all possible causes based on matching current and historical accident circumstances. Additionally, weighting factors may be available and adjusted over time for accurate accident detection. A possible cause comprising a greatest weighting factor may be used to identify a most likely cause.

Automated vehicular accident detection

Data sources containing a plurality of health information is combined throughout a plurality of travelers. Profile vectors are created from each individual member of the traveling party and a group profile vector is built as a representative whole of the traveling parties interests. Potential travel destinations vectors are clustered and mapped with dimensions comprised in the group profile vector. A recommended vacation or travel destination itinerary is proposed based on the highest overlaying dimensional score between the group profile vector and potential travel destinations.

Cognitive travel assistance

From a set of information obtained about a user, a profile is constructed representing a speech skill of the user, the set of information including audio, video, and demographic information of the user and other users, the constructing creating new data corresponding to the speech skill of the user in the profile. By correlating analytics of new real-time audio and video information with the new data in the profile, an intervention instruction is triggered automatically, the intervention being directed to change in a voice communication pattern of the user. The intervention is converted to an intervention instruction and the intervention instruction is output in a natural language form. New real-time audio and video information received in response to the spoken natural language instruction is analyzed. Responsive to the analyzing producing a change in a voice communication pattern of the user greater than a threshold change, a first state of the new data of the profile is modified to a second state in the profile.

Analytics-based speech therapy

Embodiments determine historical geographic travel data of a vehicle over a contaminant exposure time period that is inclusive of a present time; identify a contaminant that is likely located on an external surface of the vehicle as a function of historic meteorological and terrain data of the historical geographic travel data of a vehicle over a contaminant exposure time period; select a cleaning solution that is appropriate for use in cleaning the identified contaminant from the external surface of the vehicle; and drive a vehicle wash system nozzle to use the selected cleaning solution to wash the identified contaminant from the external surface of the vehicle.

Wash related to contaminant exposure time

Systems and methods for determining advertisement content based on cluster density analysis of advertisement targets within a dynamic visibility fence are disclosed. A computer-implemented method includes determining, by an advertisement determination device, a dynamic visibility fence for a time, the dynamic visibility fence defining a first set of advertisement targets, determining, by the advertisement determination device, an advertisement to display based on cluster analysis of the first set of advertisement targets, and displaying, by the advertisement determination device, the determined advertisement.

Determining advertisement content based on cluster density within dynamic visibility fence

A computer-implemented method comprising: presenting, by a computing device, an advertisement on a first device; monitoring, by the computing device, viewing activity by a user of the advertisement, wherein the monitoring comprises tracking an amount of time that the user actively views the advertisement on the first device; and continuing, by the computing device, playback of the advertisement on one or more second devices until the user has actively viewed the advertisement for a target impression time based on the monitoring.

Continuing playback of advertisements across multiple devices based on monitoring user active viewing duration

Systems and methods for providing a food product recommendation are disclosed. A computer-implemented method includes: determining, by a computing device, that a user with a mobile device enters a store; obtaining, by the computing device, user data that is based on wearable health data, taste data, and preference data of the user; obtaining, by the computing device, store data for plural food products; determining, by the computing device, a recommended food product from the plural food products based on comparing the user data to the store data; and providing, by the computing device, an indication of the recommended one of the plural food products for display on the mobile device of the user. The user data may be that of a single user or plural users, such as a family.

In-store real-time food item selection recommendations

For targeted presentation of information on a mobile device, a presence of the device is detected at a given time at in a zone. A pause is detected in a movement of the device in the zone. A hangout pattern of the device is predicted. The hangout pattern includes an expected pause duration of the pause. Using the hangout pattern and the detected pause, a time is computed to present a content on the device. The content presented at the time is expected to have a higher than a threshold probability of receiving an input at the device. The content is selected according to the probability of receiving the input. The content is transmitted to the device such that the content is available for presenting at the device at the computed time.

Growing community of inventors

Denver, CO, United States of America

Norbert Herman