Automatically clustering web pages into semantic groups promises improved search and browsing on the web. In this paper, we demonstrate how user-generated tags from largescale soc...
Daniel Ramage, Paul Heymann, Christopher D. Mannin...
As processors continue to exploit more instruction level parallelism, a greater demand is placed on reducing the e ects of memory access latency. In this paper, we introduce a nov...
Most existing work on Privacy-Preserving Data Mining (PPDM) focus on enabling conventional data mining algorithms with the ability to run in a secure manner in a multi-party setti...
The ability to aggregate huge volumes of queries over a large population of users allows search engines to build precise models for a variety of query-assistance features such as ...
Recently, the practice of speculation in resolving data dependences has been studied as a means of extracting more instruction level parallelism (ILP). An outcome of an instructio...