Microsoft Technology Licensing, LLC

Himesh Shah

Pamela Bhattacharya

Ganesh Pandey

Burra Gopal

Rolando Jimenez Salgado

David Koronthaly

Sushil Kumar

Ryan Antoine Nakhoul

Reid Joseph Kuhn

Ashish Kumar Singhal

Jagdish Singh

Rakesh Gupta

Satish Kumar Chittamuru

Tachen Chester Ni

Sai Shankar

Kang Su Gatlin

Altaf A Gilani

Christian A Gschwend

Arvind Kumar Krishnan

Ryan P DiCicco

Boulland Wang

Shireen Z Asous

Ronen Yacobi

Christina S Gentile

Shyam Sundar Jayshankar

Techniques described herein are directed to a sentiment analysis engine for classifying and quantifying customer sentiments between a customer and an agent. The sentiment analysis engine includes a data acquisition engine configured to receive data from a plurality of different communication channels. A preprocessing engine of the sentiment analysis engine is configured to apply rule(s) that are configured to perform formatting and/or filtering operations on the received data and/or isolate customer-provided messages from agent-provided messages. A customization engine of the sentiment analysis engine is configured to perform channel-specific customizations on the received data, such as, but not limited to interpreting the data in a channel-specific manner A batch scoring engine of the sentiment analysis engine is configured to quantify customer sentiments in real-time (e.g., during a communication session between the customer and agent), and such sentiments may be displayed via a GUI utilized by an authorized individual.

Multi-channel customer sentiment determination system and graphical user interface

Service issues predicted by detecting anomalies in an event signal is provided. An application such as a signal analysis application receives an event signal for analysis. The event signal includes events captured during a time period. The event signal is processed to generate a trend line. The trend line includes a best fit line transposed across averages of number of events of each data point across the time period. The number of events of an end data point may be compared to an upper confidence score and a lower confidence score associated with the end data point on the trend line. In response to detecting the number of events of the end data point exceed the upper confidence score, a notification is transmitted to a stakeholder associated with the event signal. The notification may describe a symptom associated with the number of events on the end data point.

Predicting service issues by detecting anomalies in event signal

A test executor for testing an application programming interface of a software application includes a plurality of invokers, a mapper/converter, and a comparer. The plurality of invokers includes a software application invoker and a database application invoker. The software application invoker is adapted to communicate with a software application through an application programming interface of the software application while the database application invoker is adapted to communicate with a database application through an application programming interface of the database application. The mapper/converter is in communication with the plurality of invokers. The mapper/converter converts results from at least one of the software application invoker and the database application invoker into a common data format. The comparer is in communication with the mapper/converter and compares the results in the common data format to assess the functionality of the application programming interface of the software application.

Framework for testing API of a software application

Recurring appointment items in a calendaring application are synchronized and recorded in a backend Line Of Business (LOB) service. Items marked in the calendaring application for time recording are used to create a recurring bound item with extended properties. A sweeper module scans on every run the mailbox for such recurring bound items. Occurrences of bound recurring appointments, which occur between the last scan and the current scan, are determined and detached from the corresponding recurring series, such that standalone bound items, are created for such occurrences that can be recognized by an LOB application. Entries for bound items are retrieved from a client data store and synchronized it with the backend LOB service through a create, update, or delete operation request.

Achieving recurring item recordings from calendaring applications over LOB systems

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Bothell, WA, United States of America

Himesh Shah