Gopi Chand Nutakki

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We describe the methodology that we followed to automatically extract topics corresponding to known events provided by the SNOW 2014 challenge in the context of the SocialSensor project. A data crawling tool and selected filtering terms were provided to all the teams. The crawled data was to be divided in 96 (15-minute) timeslots spanning a 24 hour period(More)
In this paper, we describe our solution to the RecSys2014 challenge and results on the test set. We briefly describe some of the challenges, then describe the methodology which starts with feature extraction and construction using the provided tweet data, in combination with IMDB as an external source. Feature construction also involved computing similarity(More)
Online third party marketplaces link buyers and sellers by providing a neutral platform for exchange. However, this requires buyers to assess the quality of goods without being able to handle or sample them. Recent research has proposed extending the warranting principle, an emerging theory of online interpersonal impression formation, to the judgements(More)
Continuous social text streams, such as tweets, provide a timeline of discussions. Topic modeling techniques such as Latent Dirichlet Allocation (LDA) have been used to extract the topics being discussed on social media streams. Recently, Online LDA has been proposed as a fast alternative for topic extraction, based on on-line stochastic optimization, while(More)
We present a new algorithm for discovering clusters in noisy data streams using dynamic and cluster-specific temporal decay factors. Our improvement helps identify and adapt to evolving trends by adapting the weighting of stream data based on both content attributes and temporal arrival patterns. Our experimental results show that the proposed algorithm can(More)
The magnetic resonance imaging (MRI) is a diagnostic and treatment evaluation tool which is very widely used in various areas of medicine. MRI images provide very high quality images of the brain tissue and so can be used to study the brain conditions. This research paper proposes a productive technique to classify brain MRI images. Examining the MRI brain(More)
The way a human brain functions is a great wonder. Numerous diseases evolve in different sections of the brain causing various functions of human body to halt. Manual detection of brain diseases is becoming a bottleneck under the circumstance of high throughput and the complexity of brain images. Automatic recognition based on the appearances of the brain(More)
Topic Models are statistical models that can be used for discovering the abstract “topics” that may occur in a text corpus, however they face dramatic challenges when coping with very sparse and yet topically diverse micro-blog posts such as tweets. In such streams, not only are the topics very diverse, but also the vocabulary is huge, making(More)
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