Learn More
Syntax-based statistical machine translation (MT) aims at applying statistical models to structured data. In this paper, we present a syntax-based statistical machine translation system based on a prob-abilistic synchronous dependency insertion grammar. Synchronous dependency insertion grammars are a version of synchronous grammars defined on dependency(More)
YouTube uploaders are the central agents in the YouTube phenomenon. We conduct extensive measurement and analysis of YouTube uploaders. We estimate YouTube scale and examine the uploading behavior of YouTube users. We demonstrate the positive reinforcement between on-line social behavior and uploading behavior. Furthermore, we examine whether YouTube users(More)
This paper introduces a grammar formalism specifically designed for syntax-based statistical machine translation. The synchronous grammar formalism we propose in this paper takes into consideration the pervasive structure divergence between languages , which many other synchronous grammars are unable to model. A Dependency Insertion Grammars (DIG) is a(More)
Structural divergence presents a challenge to the use of syntax in statistical machine translation. We address this problem with a new algorithm for alignment of loosely matched non-isomorphic dependency trees. The algorithm selectively relaxes the constraints of the two tree structures while keeping computational complexity polynomial in the length of the(More)
The rise of smart phone usage has led to an increase in the number of applications that make use of the users' locations. One popular class of such applications is location-based social discovery (LBSD), which enables users to discover others nearby and then communicate. In this paper, we show how LBSD applications can be exploited by even weak adversaries(More)
We examine third-party Online Social Network (OSN) applications for two major OSNs: Facebook and RenRen. These third-party applications typically gather, from the OSN, user personal information. We develop a measurement platform to study the interaction between OSN applications and fourth parties. We use this platform to study the behavior of 997 Facebook(More)
Lawmakers, children's advocacy groups and modern society at large recognize the importance of protecting the Internet privacy of minors (under 18 years of age). Online Social Networks, in particular, take precautions to prevent third parties from using their services to discover and profile minors. These precautions include banning young children from(More)