The location pro les of social media users are valuable for various applications, such as marketing and real-world anal- ysis. As most users do not disclose their home locations, the problem of inferring home locations has been well stud- ied in recent years. In fact, most existing methods perform batch inference using static (i.e., pre-stored) social media contents. However, social... Read More

On-line transaction processing (OLTP) is one of the two most important enterprise data management applications. Transaction processing workloads typically exhibit high concurrency and provide ample opportunities for parallel execution by multicore hardware. Unfortunately, due to the characteristics of the application, transaction processing systems must moderate and coordinate communication between independent agents. As a result, transaction processing systems cannot always convert... Read More

Web data are commonly processed using thousands of CPU cores, and large-scale scientific simulations are quickly approaching the one million CPU core mark. At this scale, the barrier to efficient data analysis is commonly the limited bandwidth to the disk. The growing main memory capacities allow data to be intelligently reduced, analyzed and transformed in situ, before being written to... Read More

The Cloudera Impala project is pioneering the next generation of Hadoop capabilities: the convergence of fast SQL queries with the capacity, scalability, and flexibility of a Hadoop cluster. With Impala, the academic and Hadoop communities now have an open-sourced codebase that helps query data stored in HDFS and Apache HBase in real time, using familiar SQL syntax. In contrast with... Read More

Abstract: How can we detect suspicious users in large online networks? Online popularity of a user or product (via follows, page-likes, etc.) can be monetized on the premise of higher ad click-through rates or increased sales. Web services and social networks which incentivize popularity thus suffer from a major problem of fake connections from link fraudsters looking to make a... Read More

Predictive modeling plays an important role in biomedical research. Thanks to the explosion of Electronic Heart Records (EHR), the interest of building predictive models using EHR data has skyrocketed in recent years. However, the methodologies for develop a predictive model are still labor intensive and ad-hoc. Such rudimentary approaches have hindered the quality and throughput of healthcare and biomedical research.... Read More

This talk will discuss how B-trees, Log-Structured Merge Trees and Streaming B-trees operate, and what is their asymptotic performance. Read More

Big data processing can be expensive and slow, a problem made worse when your data set keeps changing, forcing you to reanalyze it repeatedly. Incremental computation can speed things up by minimizing the work that must be done to update output in response to changing input, but many previous efforts at incremental computation have been limited in the algorithms they... Read More

MongoDB is the next-generation database that helps businesses transform their industries by harnessing the power of data. The world’s most sophisticated organizations, from cutting-edge startups to the largest companies, use MongoDB to create applications never before possible at a fraction of the cost of traditional databases. This talk will review the feature set of MongoDB and the history and rationale... Read More

Online gaming is one of the largest industries on the Internet, generating tens of billions of dollars in revenues annually. One core problem in online game is to find and convert free users into paying customers, which is of great importance for the sustainable development of almost all online games. Although much research has been conducted, there are still several... Read More