International Business Machines Corporation

Sonia Lynette Sequeira

Hemant Kumar Sivaswamy

Sonal Bhatt

Priyam Aneja

Laxmi V Bhatt

Meghali V Munoli

Sachin K Mahajan

Chandrashekhar K Jain

Xinyi Xu

Rohan M Jamdar

Nidhi S Kulkarni

According to an embodiment of the present invention, a plurality of networked sensing devices monitor one or more activities of a first user, wherein the one or more activities of the first user are associated with a subject area. Information associated with the one or more activities of the first user from the plurality of networked sensing devices is analyzed to determine a level of expertise of the first user with respect to the subject area. A review by the first user is generated for an item offered on a network site, wherein the item pertains to the subject area. The item is displayed on the network site with the review and determined level of expertise of the first user in response to a search for the item for a second user.

Measuring user expertise utilizing networked sensing devices

Methods, systems and computer program products for remotely determining a suitable item are provided. Aspects include registering a plurality of Internet-of-Things (IoT) devices. Aspects also include receiving sensor data from the plurality of IoT devices. The sensor data is associated with a plurality of owned objects in a vicinity of the plurality of IoT devices. Aspects also include creating an owned object registry based on the sensor data. The owned object registry includes physical attributes of each of the plurality of owned objects. Aspects also include determining an object of interest based on monitoring of a user's interactions with a website. Aspects also include determining a degree of suitability between the object of interest and one or more of the plurality of owned objects based on the owned object registry. Aspects also include transmitting a notification of the degree of suitability to a user device for display.

Remote determination of a suitable item

One or more processors divide an OLAP cube into one or more cubelets. One or more processors determine a weight corresponding to each node present within each of the one or more cubelets. One or more processors determine a total cost corresponding to each of the one or more cubelets. One or more processors assign execution of a portion of a workload corresponding to each of the one or more cubelets to a data processing element. The assignment of the execution of the portion of the workload corresponding to a cubelet to a data processing element is based on the determined total cost corresponding to the cubelet.

OLAP engine workload distribution using cost based algorithms

Provided are systems, methods, and media for identifying and purging unwanted contacts. An example method includes monitoring electronic group communication that is conducted between two or more people and building a persona profile for a person of the electronic group communication during a first period of time based, at least in part, on extracting during the first period of time, from the monitored electronic group communication, behavior data associated with a first contact number. The method includes detecting, during a second period of time, whether the person associated with the first contact number has changed. The method includes transmitting an alert to at least one person of the two or more people indicating that the person associated with the first contact number has changed.

Identifying and purging unwanted contacts from a contact list based on the construction of a persona profile

A method for comparing and analyzing data based on data analysis reports is provided. The method may include receiving a first dataset. The method may also include identifying a first portion of the first dataset and a second portion of the first dataset. Additionally, the method may include comparing and analyzing the first portion of the first dataset with the second portion of the first dataset. The method may also include receiving a second dataset from a location different from the first dataset. The method may further include comparing and analyzing the first portion and second portion of the first dataset with the second dataset. The method may also include receiving a plurality of first analysis results and a plurality of second analysis results based on the comparisons and the analyses. The method may also include presenting the plurality of first analysis results and the plurality of second analysis results.

Data comparison and analysis based on data analysis reporting

A method for comparing and analyzing data based on data analysis reports is provided. The method may include receiving a first dataset. The method may also include identifying a first portion of the first dataset and a second portion of the first dataset. Additionally, the method may include comparing and analyzing the first portion of the first dataset with the second portion of the first dataset. The method may also include receiving a second dataset from a location different from the first dataset. The method may further include comparing and analyzing the first portion and second portion of the first dataset with the second dataset. The method may also include receiving a plurality of first analysis results and a plurality of second analysis results based on the comparisons and the analyzes. The method may also include presenting the plurality of first analysis results and the plurality of second analysis results.

A method for generating an output of users that are communicating online in which one or more processors gathers data of topics of interest for each group member. One or more processors receive content of an online communication session and sends the content to a cognitive engine to determine the topic and summary information of the session. The cognitive engine sends the topic to a graphic engine to obtain a pictorial representation of the topic. One or more processors receive the summary information and pictorial representation and generates personalizes summaries for the group members based on the interests determined for each group member from prior online sessions.

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Pune, India

Sonia Lynette Sequeira