Short Message Service (SMS) is one of the most frequently used services in the mobile phones, next to calls. In developing countries like India, SMS is the cheapest mode of communication. The advantage of this fact is exploited by the advertising companies to reach masses. The unsolicited SMS messages (a.k.a. spam SMS) generates notifications, thus consuming precious user attention. To formulate spam SMS problem and understand user's needs and preceptions, we conducted an online survey with 458 participants in different cities of India. Most of the survey participants admitted that they are quite annoyed with burst of SMS spams and in-effectiveness of regulatory solutions. However, some participants reported that, they do get useful information from spam SMSes sometime(e.g. discounts at a popular food joint). In this paper, we present design and implementation of a user-centric spam SMS filtering application i.e. SMSAssassin that uses content based machine learning techniques with user generated features to filter unwanted SMSes and reduces the burden of notifications for a mobile user.