Research Interest

Data Mining: Analysis of data is a process of inspecting, cleaning, transforming, and modeling data with the goal of discovering useful information, suggesting conclusions, and supporting decision-making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, in different business, science, and social science domains. Data mining is a particular data analysis technique that focuses on modeling and knowledge discovery for predictive rather than purely descriptive purposes. Business intelligence covers data analysis that relies heavily on aggregation, focusing on business information.

Text Analytics: I have been working on tasks like Sentiment Analysis, Information Extraction, Classification and Clustering Algorithms and Social Media Text Analysis for last 4 years. I am working in a developed and coordinated a Text Analytics laboratory, which works in various text analytics tasks. I have also been an organizing member of Text Analytics workshops since 2013 (www.textanalytics.in). Mining scientific publications is another important area I am interested in.

Scientometrics: My interest in Scientometrics revolves around the intersection of information retrieval and scientometrics. It is fascinating to explore how scientometrics can contribute to information retrieval research, particularly in scholarly article domain. I also take interest in computational analysis of bibliometric data for mapping research competence of institutions/ countries, identifying thematic research trends in different disciplines and development of appropriate research performance ranking systems. A complete implementation of our work is implemented and deployed on www.universityselectplus.com.

Sentiment Analysis: Sentiment analysis (also known as opinion mining) refers to the use of natural language processing, text analysis and computational linguistics to identify and extract subjective information in source materials. Sentiment analysis is widely applied to reviews and social media for a variety of applications, ranging from marketing to customer service. Generally speaking, sentiment analysis aims to determine the attitude of a speaker or a writer with respect to some topic or the overall contextual polarity of a document.