World Wide Web acts as one of the major sources of information for health related questions. However, often, there are multiple conflicting answers to a single question and it is hard to come up with “a single best correct answer”. Therefore, it is highly desirable to identify conflicting perspectives about a particular question (or topic). In this paper, we have described our participation in Consumer Health Information System(CHIS) task at FIRE 2016. There were two sub-tasks in this contest. The first sub-task deals with identifying if a particular answer is relevant to a given question. The second sub-task deals with detecting if a particular answer agrees or refuses the claim posed in a given question. We pose both these tasks as supervised pair classification tasks. We report our results for various document representations and classification algorithms.