Microsoft Technology Licensing, LLC

Adam Edward Shirey

Emmanouil Koukoumidis

Daniel Massey

Donald Frank Brinkman, Jr

Ying Wang

Dustin Isaac Abramson

Qi Yao

Anna Swanson Bertiger

Scott A Schwarz

Hudong Wang

Michael Andrews

Cezar Augusto Alevatto Guimaraes Neto

Kelli A Stuckart

Maria Alexandropoulou

Alexander V Moore

Brian J Alseth

Richard P Lozada

Anthony Turner

Sergei Tuterov

Daniel Lee Massey

Examples for detecting anomalies in a dataset are provided herein. A decision tree is trained using the data set and partitions of the data set produced by the trained decision tree are identified. Further, subsets of data based at least on the partitions of the data set are identified and z-scores are computed for the subsets of data. Based at least on the subsets of data, a subset of data with a highest z-score is identified as an anomalous subset of data, and the anomalous subset of data is provided for display.

Tree-based anomaly detection

Systems and methods for receiving various input data, processing said input data, and utilizing artificial emotional intelligence to analyze said input data to return calculated response stimuli are provided. Various electronic devices may be utilized to acquire input data related to a specific user, a group of users, or environments. This input data, which may comprise tone of voice, facial expressions, social media profiles, and surrounding environmental data, may be compared with past data related to a certain user, group of users, or environment. The systems and methods herein may employ artificial emotional intelligence to evaluate the aggregated data and provide a response stimulus to a user or group of users. The response stimulus may be in the form of uplifting/encouraging music, quotes, pictures, jokes, suggestions, etc. The purpose of providing the response stimuli is to significantly increase the productivity of meetings, conversations, and other interactions across electronic devices.

EQ-digital conversation assistant

A server device configured to execute an electronic data analysis platform program to store a plurality of modular data processing tools, each modular data processing tool configured to perform data processing with predetermined data types and to combine with other modular data processing tools in a data analysis pipeline, receive a user input of one or more user data sources, map the data of the one or more user data sources to one or more of the predetermined data types, determine a data analytic goal for the mapped one or more user data sources, select one or more modular data processing tools configured to process the one or more predetermined data types mapped to data of the mapped one or more user data sources to generate the data analytic goal, and generate a data analysis pipeline configured to generate the data analytic goal.

Modular electronic data analysis computing system

Growing community of inventors

Renton, WA, United States of America

Adam Edward Shirey