Search Results - "2014 IEEE International Conference on Big Data (Big Data)"

Immersive and collaborative data visualization using virtual reality platforms by Donalek, Ciro, Djorgovski, S. G., Cioc, Alex, Wang, Anwell, Zhang, Jerry, Lawler, Elizabeth, Yeh, Stacy, Mahabal, Ashish, Graham, Matthew, Drake, Andrew, Davidoff, Scott, Norris, Jeffrey S., Longo, Giuseppe

“…Effective data visualization is a key part of the discovery process in the era of "big data". It is the bridge between the quantitative content of the data and…”
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Geotagging one hundred million Twitter accounts with total variation minimization by Compton, Ryan, Jurgens, David, Allen, David

“…Geographically annotated social media is extremely valuable for modern information retrieval. However, when researchers can only access publicly-visible data,…”
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Scaling up M-estimation via sampling designs: The Horvitz-Thompson stochastic gradient descent by Clemencon, Stephan, Bertail, Patrice, Chautru, Emilie

“…In certain situations that shall be undoubtedly more and more common in the Big Data era, the datasets available are so massive that computing statistics over…”
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Optimizing load balancing and data-locality with data-aware scheduling by Ke Wang, Xraobing Zhou, Tonglin Li, Dongfang Zhao, Lang, Michael, Raicu, Ioan

“…Load balancing techniques (e.g. work stealing) are important to obtain the best performance for distributed task scheduling systems that have multiple…”
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FusionFS: Toward supporting data-intensive scientific applications on extreme-scale high-performance computing systems by Dongfang Zhao, Zhao Zhang, Xiaobing Zhou, Tonglin Li, Ke Wang, Kimpe, Dries, Carns, Philip, Ross, Robert, Raicu, Ioan

“…State-of-the-art, yet decades-old, architecture of high-performance computing systems has its compute and storage resources separated. It thus is limited for…”
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Spatial big data analytics of influenza epidemic in Vellore, India by Lopez, Daphne, Gunasekaran, M., Murugan, B. Senthil, Kaur, Harpreet, Abbas, Kaja M.

“…The study objective is to develop a big spatial data model to predict the epidemiological impact of influenza in Vellore, India. Large repositories of…”
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Large-scale logistic regression and linear support vector machines using spark by Lin, Chieh-Yen, Tsai, Cheng-Hao, Ching-Pei Lee, Lin, Chih-Jen

“…Logistic regression and linear SVM are useful methods for large-scale classification. However, their distributed implementations have not been well studied…”
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Analyzing the language of food on social media by Fried, Daniel, Surdeanu, Mihai, Kobourov, Stephen, Hingle, Melanie, Bell, Dane

“…We investigate the predictive power behind the language of food on social media. We collect a corpus of over three million food-related posts from Twitter and…”
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Knowledge-based clustering of ship trajectories using density-based approach by Bo Liu, de Souza, Erico N., Matwin, Stan, Sydow, Marcin

“…Maritime traffic monitoring is an important aspect of safety and security, particularly in close to port operations. While there is a large amount of data with…”
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Empowering personalized medicine with big data and semantic web technology: Promises, challenges, and use cases by Panahiazar, Maryam, Taslimitehrani, Vahid, Jadhav, Ashutosh, Pathak, Jyotishman

“…In healthcare, big data tools and technologies have the potential to create significant value by improving outcomes while lowering costs for each individual…”
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BurstMem: A high-performance burst buffer system for scientific applications by Teng Wang, Oral, Sarp, Yandong Wang, Settlemyer, Brad, Atchley, Scott, Weikuan Yu

“…The growth of computing power on large-scale systems requires commensurate high-bandwidth I/O systems. Many parallel file systems are designed to provide fast…”
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Handling smart environment devices, data and services at the semantic level with the FI-WARE core platform by Ramparany, Fano, Galan Marquez, Fermin, Soriano, Javier, Elsaleh, Tarek

“…The development of IoT (Internet of Things) applications poses a number of scientific and technological challenges which stem from the characteristics of the…”
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ParK: An efficient algorithm for k-core decomposition on multicore processors by Dasari, Naga Shailaja, Desh, Ranjan, Zubair, M.

“…The k-core of a graph is the largest induced subgraph with minimum degree k. The k-core decomposition is to find the core number of each vertex in a graph,…”
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Synthetic data generation for the internet of things by Anderson, Jason W., Kennedy, K. E., Ngo, Linh B., Luckow, Andre, Apon, Amy W.

“…The concept of Internet of Things (IoT) is rapidly moving from a vision to being pervasive in our everyday lives. This can be observed in the integration of…”
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PuLP: Scalable multi-objective multi-constraint partitioning for small-world networks by Slota, George M., Madduri, Kamesh, Rajamanickam, Sivasankaran

“…We present PuLP, a parallel and memory-efficient graph partitioning method specifically designed to partition low-diameter networks with skewed degree…”
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Large-scale network traffic monitoring with DBStream, a system for rolling big data analysis by Bar, Arian, Finamore, Alessandro, Casas, Pedro, Golab, Lukasz, Mellia, Marco

“…The complexity of the Internet has rapidly increased, making it more important and challenging to design scalable network monitoring tools. Network monitoring…”
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An intelligent machine monitoring system for energy prediction using a Gaussian Process regression by Bhinge, Raunak, Biswas, Nishant, Dornfeld, David, Jinkyoo Park, Law, Kincho H., Helu, Moneer, Rachuri, Sudarsan

“…Recent advances in machine automation and sensing technology offer new opportunities for continuous condition monitoring of an operating machine. This paper…”
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Dynamic pre-training of Deep Recurrent Neural Networks for predicting environmental monitoring data by Ong, Bun Theang, Sugiura, Komei, Zettsu, Koji

“…In this paper, we introduce a Deep Recurrent Neural Network (DRNN) that is trained using a novel autoencoder pre-training method especially designed for the…”
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Increasing the veracity of event detection on social media networks through user trust modeling by Bodnar, Todd, Tucker, Conrad, Hopkinson, Kenneth, Bilen, Sven G.

“…With the success and ubiquity of large scale, social media networks comes the challenge of assessing the veracity of information shared across them that inform…”
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Big Automotive Data: Leveraging large volumes of data for knowledge-driven product development by Johanson, Mathias, Belenki, Stanislav, Jalminger, Jonas, Fant, Magnus, Gjertz, Mats

“…To be successful in the increasingly competitive consumer vehicle market, automotive manufacturers must be highly responsive to customer needs and market…”
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