Forum for Science, Industry and Business

Sponsored by:     3M 
Search our Site:


Researchers Develop Techniques for Computing Google-Style Web Rankingsup to Five Times Faster


Speed-up may make "topic-sensitive" page rankings feasible

Computer science researchers at Stanford University have developed several new techniques that together may make it possible to calculate Web page rankings as used in the Google search engine up to five times faster. The speed-ups to Google’s method may make it realistic to calculate page rankings personalized for an individual’s interests or customized to a particular topic.

The Stanford team includes graduate students Sepandar Kamvar and Taher Haveliwala, noted numerical analyst Gene Golub and computer science professor Christopher Manning. They will present their first paper at the Twelfth Annual World Wide Web Conference (WWW2003) in Budapest, Hungary, May 20-24, 2003. The work was supported by the National Science Foundation (NSF), an independent federal agency that supports fundamental research and education in all fields of science and engineering.

Computing PageRank, the ranking algorithm behind the Google search engine, for a billion Web pages can take several days. Google currently ranks and searches 3 billion Web pages. Each personalized or topic-sensitive ranking would require a separate multi-day computation, but the payoff would be less time spent wading through irrelevant search results. For example, searching a sports-specific Google site for "Giants" would give more importance to pages about the New York or San Francisco Giants and less importance to pages about Jack and the Beanstalk.

"This work is a wonderful example of how NSF support for basic computer science research, including applied mathematics and algorithm research, has impacts in daily life," said NSF program officer Maria Zemankova. In the mid-1990s, an NSF digital library project and an NSF graduate fellowship also supported Stanford graduate students Larry Page and Sergey Brin while they developed what would become the Google search engine.

To speed up PageRank, the Stanford team developed a trio of techniques in numerical linear algebra. First, in the WWW2003 paper, they describe so-called "extrapolation" methods, which make some assumptions about the Web’s link structure that aren’t true, but permit a quick and easy computation of PageRank. Because the assumptions aren’t true, the PageRank isn’t exactly correct, but it’s close and can be refined using the original PageRank algorithm. The Stanford researchers have shown that their extrapolation techniques can speed up PageRank by 50 percent in realistic conditions and by up to 300 percent under less realistic conditions.

A second paper describes an enhancement, called "BlockRank," which relies on a feature of the Web’s link structure-a feature that the Stanford team is among the first to investigate and exploit. Namely, they show that approximately 80 percent of the pages on any given Web site point to other pages on the same site. As a result, they can compute many single-site PageRanks, glue them together in an appropriate manner and use that as a starting point for the original PageRank algorithm. With this technique, they can realistically speed up the PageRank computation by 300 percent.

Finally, the team notes in a third paper that the rankings for some pages are calculated early in the PageRank process, while the rankings of many highly rated pages take much longer to compute. In a method called "Adaptive PageRank," they eliminate redundant computations associated with those pages whose PageRanks finish early. This speeds up the PageRank computation by up to 50 percent.

"Further speed-ups are possible when we use all these methods," Kamvar said. "Our preliminary experiments show that combining the methods will make the computation of PageRank up to a factor of five faster. However, there are still several issues to be solved. We’re closer to a topic-based PageRank than to a personalized ranking."

The complexities of a personalized ranking would require even greater speed-ups to the PageRank calculations. In addition, while a faster algorithm shortens computation time, the issue of storage remains. Because the results from a single PageRank computation on a few billion Web pages require several gigabytes of storage, saving a personalized PageRank for many individuals would rapidly consume vast amounts of storage. Saving a limited number of topic-specific PageRank calculations would be more practical.

The reason for the expensive computation and storage requirements lies in how PageRank generates the rankings that have led to Google’s popularity. Unlike page-ranking methods that rate each page separately, PageRank bases each page’s "importance" on the number and importance of pages that link to the page.

Therefore, PageRank must consider all pages at the same time and can’t easily omit pages that aren’t likely to be relevant to a topic. It also means that the faster method will not affect how quickly Google presents results to users’ searches, because the rankings are computed in advance and not at the time a search is requested.

The Stanford team’s conference paper and technical reports on enhancing the PageRank algorithm, as well as the original paper describing the PageRank method, are available on the Stanford Database Group’s Publication Server (

David Hart | National Science Foundation
Further information:

More articles from Information Technology:

nachricht Snake-inspired robot uses kirigami to move
22.02.2018 | Harvard John A. Paulson School of Engineering and Applied Sciences

nachricht Camera technology in vehicles: Low-latency image data compression
22.02.2018 | Fraunhofer-Institut für Nachrichtentechnik, Heinrich-Hertz-Institut, HHI

All articles from Information Technology >>>

The most recent press releases about innovation >>>

Die letzten 5 Focus-News des innovations-reports im Überblick:

Im Focus: Attoseconds break into atomic interior

A newly developed laser technology has enabled physicists in the Laboratory for Attosecond Physics (jointly run by LMU Munich and the Max Planck Institute of Quantum Optics) to generate attosecond bursts of high-energy photons of unprecedented intensity. This has made it possible to observe the interaction of multiple photons in a single such pulse with electrons in the inner orbital shell of an atom.

In order to observe the ultrafast electron motion in the inner shells of atoms with short light pulses, the pulses must not only be ultrashort, but very...

Im Focus: Good vibrations feel the force

A group of researchers led by Andrea Cavalleri at the Max Planck Institute for Structure and Dynamics of Matter (MPSD) in Hamburg has demonstrated a new method enabling precise measurements of the interatomic forces that hold crystalline solids together. The paper Probing the Interatomic Potential of Solids by Strong-Field Nonlinear Phononics, published online in Nature, explains how a terahertz-frequency laser pulse can drive very large deformations of the crystal.

By measuring the highly unusual atomic trajectories under extreme electromagnetic transients, the MPSD group could reconstruct how rigid the atomic bonds are...

Im Focus: Developing reliable quantum computers

International research team makes important step on the path to solving certification problems

Quantum computers may one day solve algorithmic problems which even the biggest supercomputers today can’t manage. But how do you test a quantum computer to...

Im Focus: In best circles: First integrated circuit from self-assembled polymer

For the first time, a team of researchers at the Max-Planck Institute (MPI) for Polymer Research in Mainz, Germany, has succeeded in making an integrated circuit (IC) from just a monolayer of a semiconducting polymer via a bottom-up, self-assembly approach.

In the self-assembly process, the semiconducting polymer arranges itself into an ordered monolayer in a transistor. The transistors are binary switches used...

Im Focus: Demonstration of a single molecule piezoelectric effect

Breakthrough provides a new concept of the design of molecular motors, sensors and electricity generators at nanoscale

Researchers from the Institute of Organic Chemistry and Biochemistry of the CAS (IOCB Prague), Institute of Physics of the CAS (IP CAS) and Palacký University...

All Focus news of the innovation-report >>>



Industry & Economy
Event News

2nd International Conference on High Temperature Shape Memory Alloys (HTSMAs)

15.02.2018 | Event News

Aachen DC Grid Summit 2018

13.02.2018 | Event News

How Global Climate Policy Can Learn from the Energy Transition

12.02.2018 | Event News

Latest News

Basque researchers turn light upside down

23.02.2018 | Physics and Astronomy

Finnish research group discovers a new immune system regulator

23.02.2018 | Health and Medicine

Attoseconds break into atomic interior

23.02.2018 | Physics and Astronomy

Science & Research
Overview of more VideoLinks >>>