Hadoop and Natural Language Processing Based Analysis on Kisan Call Center (KCC) Data

Call Centers have always played a highly significant role in the service industry, from retail to technical support. Government of India (GOI) has launched Kisan Call Centers (KCC) across the country to deliver extension services to the farming community for resolving their diverse problems. Every time a farmer makes a call, the query asked by the farmer is recorded manually and the number of calls generated in a day will be many and that leads to Big Data. As the questions asked by farmers are recorded manually, the same question asked by different farmers can be framed differently in terms of the words used for the query. The idea of this paper is to analyze the large KCC datasets using Hadoop based MapReduce algorithms to draw interesting insights such as the hour during which highest number of calls are made, the crop which has been questioned a lot by farmers and use Natural Language Processing (NLP) techniques to group the similar queries to know which queries are frequently asked by farmers, project these findings graphically.