Research Area
Year Published

1012 Results

December 1, 2011

Performance of an online translation tool when applied to patient educational material

Journal of Hospital Medicine

We evaluate the accuracy of state-of-the-art online machine translation systems for translating patient educational material.

By: Raman R. Khanna, Leah S. Karliner, Matthias Eck, Eric Vittinghoff, Christopher J. Koenig, Margaret C. Fang

August 15, 2011

Phonetic Classification Using Controlled Random Walks

Conference of the International Speech Communication Association (Interspeech)

Recently, semi-supervised learning algorithms for phonetic classifiers have been proposed that have obtained promising results. Often, these algorithms attempt to satisfy learning criteria that are not inherent in the standard generative or discriminative training procedures for phonetic classifiers.

By: Katrin Kirchhoff, Andrei Alexandrescu

July 24, 2011

Learning Relevance from a Heterogeneous Social Network and Its Application in Online Targeting

ACM Special Interest Group on Information Retrieval (SIGIR)

The rise of social networking services in recent years presents new research challenges for matching users with interesting content. While the content-rich nature of these social networks offers many…

By: Chi Wang, Rajat Raina, David Fong, Ding Zhou, Jiawei Han, Greg Badros

July 17, 2011

Dimensions of Self-Expression in Facebook Status Updates

AAAI International Conference on Weblogs and Social Media (ICWSM)

We describe the dimensions along which Facebook users tend to express themselves via status updates using the semi-automated text analysis approach, the Meaning Extraction Method (MEM).

By: Adam D. I. Kramer, Cindy K. Chung

July 17, 2011

Center of Attention: How Facebook Users Allocate Attention across Friends

AAAI International Conference on Weblogs and Social Media (ICWSM)

An individual’s personal network — their set of social contacts — is a basic object of study in sociology. Studies of personal networks have focused on their size (the number of contacts) and their composition (in terms of categories such as kin and co-workers). Here we propose a new measure for the analysis of personal networks, based on the way in which an individual divides his or her attention across contacts. This allows us to contrast people who focus a large fraction of their interactions on a small set of close friends with people who disperse their attention more widely.

By: Lars Backstrom, Eytan Bakshy, Jon Kleinberg, Thomas Lento, Itamar Rosenn

July 5, 2011

Location3: How Users Share and Respond to Location-Based Data on Social Networking Sites

AAAI International Conference on Weblogs and Social Media (ICWSM)

In August 2010 Facebook launched Places, a location-based service that allows users to check into points of interest and share their physical whereabouts with friends. The friends who see these events in their News Feed can then respond to these check-ins by liking or commenting on them.

By: Jonathan Chang, Eric Sun

July 1, 2011

Many-core key-value store

International Green Computing Conference (IGCC)

Scaling data centers to handle task-parallel workloads requires balancing the cost of hardware, operations, and power. Low-power, low-core-count servers reduce costs in one of these dimensions, but may require additional nodes to provide the required quality of service or increase costs by underutilizing memory and other resources.

By: Mateusz Berezecki, Eitan Frachtenberg, Michael Paleczny, Ken Steele

June 20, 2011

YSmart: Yet Another SQL-to-MapReduce Translator

International Conference on Distributed Computing Systems (ICDCS)

MapReduce has become an effective approach to big data analytics in large cluster systems, where SQL-like queries play important roles to interface between users and systems. However, based on our Face book daily operation results, certain types of queries are executed at an unacceptable low speed by Hive (a production SQL-to-MapReduce translator). In this paper, we demonstrate that existing SQL-to-MapReduce translators that operate in a one-operation-to-one-job mode and do not consider query correlations cannot generate high-performance MapReduce programs for certain queries, due to the mismatch between complex SQL structures and simple MapReduce framework. We propose and develop a system called Y Smart, a correlation aware SQL-to-MapReduce translator. Y Smart applies a set of rules to use the minimal number of MapReduce jobs to execute multiple correlated operations in a complex query. Y Smart can significantly reduce redundant computations, I/O operations and network transfers compared to existing translators. We have implemented Y Smart with intensive evaluation for complex queries on two Amazon EC2 clusters and one Face book production cluster. The results show that Y Smart can outperform Hive and Pig, two widely used SQL-to-MapReduce translators, by more than four times for query execution.

By: Rubao Lee, Tian Luo, Yin Huai, Fusheng Wang, Yongqiang He, Xiaodong Zhang

June 12, 2011

Apache Hadoop goes realtime at Facebook

ACM Special Interest Group on Management of Data (SIGMOD)

Facebook recently deployed Facebook Messages, its first ever user-facing application built on the Apache Hadoop platform. Apache HBase is a database-like layer built on Hadoop designed to support billions of messages per day.

By: Dhruba Borthakur, Joydeep Sen Sarma, Jonathan Gray, Kannan Muthukkaruppan, Nicolas Spiegelberg, Hairong Kuang, Karthik Ranganathan, Dmytro Molkov, Aravind Menon, Samuel Rash, Rodrigo Schmidt, Amitanand Aiyer

April 10, 2011

Facebook Immune System

Workshop on Social Network Systems (SNS)

Popular Internet sites are under attack all the time from phishers, fraudsters, and spammers. They aim to steal user information and expose users to unwanted spam. The attackers have vast resources at their disposal. They are well-funded, with full-time skilled labor, control over compromised and infected accounts, and access to global botnets.

By: Tao Stein, Roger Chen, Karan Mangla