Faculty Publications
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Item Efficient user profiling in twitter social network using traditional classifiers(Springer Verlag service@springer.de, 2016) Raghuram, M.A.; Akshay, K.; Chandrasekaran, K.Any discussion in social media can be fruitful if the people involved in the discussion are related to a field. In a similar way to advertise an event, it is useful to find users who are interested in the content of the event. In social networks like Twitter, which contain a large number of users, the categorization of users based on their interests will help this cause. This paper presents an efficient supervised machine learning approach which categorizes Twitter users based on three important features(Tweet-based, User-based and Time-series based) into six interest categories - Politics, Entertainment, Entrepreneurship, Journalism, Science & Technology and Healthcare. We compare the proposed feature set with different traditional classifiers like Support Vector Machines, Naive-Bayes, k-Nearest Neighbours, Decision Tree and Logistic Regression, and obtain upto 89.82% accuracy in classification. We also propose a design for a real-time system for Twitter user profiling along with a prototype implementation. © Springer International Publishing Switzerland 2016.Item DANE: An inbuilt security extension(Institute of Electrical and Electronics Engineers Inc., 2016) Aishwarya, C.; Raghuram, M.A.; Hosmani, S.; Sannidhan, M.S.; Rajendran, B.; Chandrasekaran, K.; Bindhumadhava, B.S.Use of TSL and certificates in secure applications in the internet is very common today. Certificate authorities are playing the important role of trust anchors. But this means that third party certificate authorities have to be trusted by both domain owners and their clients. Compromises of certificate authorities will put many users under a huge risk. To solve this problem, the DANE protocol was proposed that is used on top of DNSSEC. It allows using the chain of trust in DNS for authenticating certificates and makes clients impose many constraints on the certificates they receive. We analyze the performance of the DANE protocol at the client side and also present a tool for deploying and administrating DANE with BIND servers in a local network. © 2015 IEEE.Item Efficient audio segmentation in soccer videos(Institute of Electrical and Electronics Engineers Inc., 2016) Raghuram, M.A.; Chavan, N.R.; Koolagudi, S.G.; Ramteke, P.B.Identifying different audio segments in videos is the first step for many important tasks such as event detection and speech transcription. Approaches using Mel-Frequency Cepstral coefficients (MFCCs) with Gaussian mixture models (GMMs) and hidden Markov models (HMMs) perform reasonably well in stationary conditions but do not scale to a broad range of environmental conditions. This paper focuses on the audio segmentation in broadcast soccer videos into audio classes such as Silence, Speech Only, Speech Over Crowd, Crowd Only and Excited, with an alternative feature set which is simplistic as well as robust to changes in the environment conditions. Support Vector Machines (SVMs), Neural Networks and Random Forest are used for the classification. The accuracy achieved with SVMs, Neural Networks and Random Forest are 83.80%, 86.07%, and 88.35% respectively. The proposed features and Random Forest classifier are found to achieve better accuracy compared to the other classifiers. © 2016 IEEE.Item Bird classification based on their sound patterns(Springer New York LLC barbara.b.bertram@gsk.com, 2016) Raghuram, M.A.; Chavan, N.R.; Belur, R.; Koolagudi, S.G.In this paper we focus on automatic bird classification based on their sound patterns. This is useful in the field of ornithology for studying bird species and their behavior based on their sound. The proposed methodology may be used to conduct survey of birds. The proposed methods may be used to automatically classify birds using different audio processing and machine learning techniques on the basis of their chirping patterns. An effort has been made in this work to map characteristics of birds such as size, habitat, species and types of call, on to their sounds. This study is also part of a broader project that includes development of software and hardware systems to monitor the bird species that appear in different geographical locations which helps ornithologists to monitor environmental conditions with respect to specific bird species. © 2016, Springer Science+Business Media New York.