Part 1: Research Activities in Text and Graph Analytics (TGA) Group in Xerox Research Centre India
Part 2: QART: A System for Real-time Holistic Quality Assurance for Contact Center Dialogues
Shourya Roy, Ph.D.
Senior Research Scientist
Xerox Research, India

Friday, Feb. 12, 2016
1–2 p.m.
Brickyard (BYENG) 210, Tempe campus [map]

Parts 1 and 2 are 25 minutes each and a Q&A will be held during the last 10 minutes.

Abstract

In the first part of this talk, I will give overview of ongoing research activities led by Text and Graph Analytics group in Xerox Research Centre India in business domains such as Customer Care and Healthcare.

In the second part, I will talk about the paper titled ” QART : A System for Real-time Holistic Quality Assurance for Contact Center Dialogues” which will be presented in AAAI 2016 conference.

Quality assurance (QA) and customer satisfaction (CSat) analysis are two commonly used practices to measure goodness of dialogues between agents and customers in contact centers. The practices however have a few shortcomings. QA puts sole emphasis on agents’ organizational compliance aspect whereas C-Sat attempts to measure customers’ satisfaction only based on post-dialogue surveys. As a result, outcome of independent QA and C-Sat analysis may not always be in correspondence. Secondly, both processes are retrospective in nature and hence, evidences of bad past dialogues (and consequently bad customer experiences) can only be found after hours or days or weeks depending on their periodicity. Finally, human intensive nature of these practices lead to time and cost overhead while being able to analyze only a small fraction of dialogues. In this paper, we introduce an automatic real-time quality assurance system for contact centers — QART (pronounced cart). QART performs multi-faceted analysis on dialogue utterances, as they happen, using sophisticated statistical and rule-based natural language processing (NLP) techniques. It covers various aspects inspired by today’s QA and C-Sat practices as well as introduces novel incremental dialogue summarization capability. QART front-end is an interactive dashboard providing views of ongoing dialogues at different granularity enabling agents’ supervisors to monitor and take corrective actions as needed. We demonstrate effectiveness of different back-end modules as well as the overall system by experimental results on a real-life contact center chat dataset.

Bio

Shourya Roy is currently a Senior Scientist at Xerox Research, India where he leads the “Text and Graph Analytics” group. In this role, Shourya is leading a group of researchers working on large scale text and graph analytics problems in domains such as outsourcing and customer care, healthcare and education. As a part of this role he also looks after research and business opportunities in customer care domain for Xerox in South-East Asia and Australia.  Shourya’s research interest spans Text and Data Mining, Natural Language Processing, Machine Learning, and Human Computation.  Over the years, Shourya’s work has led to over 25 patent disclosures and over 50 publications in premier journals and conferences such as AAAI, SIGKDD, SIGMOD, VLDB, WWW.  He has taken up different professional roles including program committee member in top ranked conferences, editor in reputed journals, reviewer of journal and conference papers, advisor to students etc. He has been associated with several workshops in renowned text, data and web mining conferences — notably, the series of “Noisy Text Analytics” (AND) workshops which he co-initiated in 2007. This year he is co-organizing two workshops viz. Network Data Analytics (NDA) with SIGMOD 2016 and Health Data Management and Mining (HDMM) with ICDE 2016.

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