The goal of a Service System in an organization is to deliver uninterrupted service towards achieving business success. Ticketing system is an example of a Service System which is responsible for handling huge volumes of tickets generated by large enterprise IT (Information Technology) infrastructure components and ensuring smooth operation. Instead of manual screening one needs to extract information automatically from them to gain insights to improve operational efficiency. To ensure better operation we propose a framework to cluster incident tickets based on their textual context that can eliminate manual classification of them, which is labor intensive and costly. Further we label each of the clusters by generating meaningful keywords as logical itemsets, extracting candidate labels from Wikipedia articles, and finally scoring each of labels against each cluster. These labels can reflect an adequate and concise specification of each cluster. Further we experiment our approach with industrial ticket data from three different domains and report on the learned experience. We believe that our framework for clustering and labeling will enable enterprises to prioritize the issues in their IT infrastructure and improve the reliability and availability of their services.