The Analytics for Services team at IRL is involved in projects related to the application of natural language processing, information retrieval, text analytics, data mining, predictive modeling, mathematical optimization, theory and algorithms, stochastic analysis, simulation, pattern recognition, statistics, machine translation, and speech technologies for enhanced service delivery.
We deal with structured data in enterprise databases, as well as with unstructured, noisy, and multi-lingual information sources such as Web pages, documents, e-mail, ticketing systems, team rooms, and IT monitoring systems.
One of our focus areas is Data Analytics (DA). We are working on various applications of deep text analytics, natural language processing, information extraction, information retrieval, machine translation, and machine learning for services businesses. Examples include developing applications of focused language translation for services, improving the organization and reuse of knowledge extracted from previous interactions to help application and IT support teams, automatically evaluating and filtering resumes of people applying for jobs using IR/IE techniques, etc.
With our Analytics for Services team, we also focus on methodologies for predictive and prescriptive analytics and applications of mathematical optimization and business analytics. Examples include developing algorithms for complex constrained combinatorial, deterministic and stochastic optimization and building models to solve workforce optimization problems such as capacity utilization, hiring and training, strategic planning and budgeting, workforce scheduling, etc., seen in large scale service delivery centers.
In the area of contact center research, we are developing an array of technologies ranging from automatic evaluation of the linguistic abilities of applicants to customer satisfaction analysis. Contact center analytics uses heterogeneous data sources such as audio conversations, agent logs, and feedback forms in order to increase productivity and generate greater insights to improve the delivery quality. In the area of speech technologies, we are working on solutions that help people access information in various forms by overcoming barriers such as physical disabilities, lack of IT skills, and illiteracy.