MEDIA CONTACT: GEORGE MCCRORY
300 Plaza Centre One
Iowa City IA 52242
(319) 384-0012; fax (319) 384-0024
RESEARCHER CONTACT: FILIPPO MENCZER
Assistant Professor of Management Sciences
Release: Jan. 9, 2003
UI researcher studies model for better web search engine results
search engines such as Google and Yahoo are effective tools for the common
World Wide Web user, there is a desire to improve upon these engines to find
pages that relate to a subject of interest. Recently published research by
Filippo Menczer, an assistant professor of Management Sciences at the University
of Iowa, explores mathematical models that could help engineers of Internet
search engines create better ways to hunt down the pages that Web users want
In his paper, "Growing and navigating the small world Web by local content,"
published in the Oct. 29 issue of Proceedings of the National Academy of Sciences,
Menczer examined a sample of 150,000 web pages, studying the relationships
between text, links and meaning. He analyzed almost 4 billion pairs of pages
with similarities. With this huge body of data, Menczer was able to discover
a mathematical power-law relationship between link probability and similarity
of language across web pages.
His model is the first to give accurate predictions of Web link structure
and growth based on the content of the Web pages. Other Internet models have
assumed that a Web page author has knowledge of every Websites popularity,
and chooses his links based on that knowledge. But Menczer says authors link
to the best and most popular pages within the same category. This creates
a small Web between pages with similar topics, like books or a hobby. Menczer's
model of this process closely matches what is seen in the real Internet.
This model may help Internet developers gain a better understanding of the
evolving structure of the Web and its cognitive and social underpinnings.
This may, in turn, lead to more effective authoring guidelines as well as
improved ranking, classification, and clustering algorithms used in Web search
"Hopefully, by analyzing the relationship between meanings of a page,
links, and words, we will be able to determine how to use these cues to find
better search results," said Menczer.
The National Science Foundation (NSF) funds Menczer's research. He is a recipient
of one of the NSF's most prestigious awards, the Early Career Development
Award, which provides project support over a five-year period. The award recognizes
and supports the early career-development activities of those teacher-scholars
who are most likely to become the academic leaders of the 21st century.
Menczer and his students developed the MySpiders system, which allows users
to launch personal adaptive agents who search the Web on their behalf. Menczer
and his Adaptive Agents Research Group at the University of Iowa pursue interdisciplinary
research projects in Web, text, and data mining, Web intelligence, distributed
information systems, adaptive intelligent agents, evolutionary computation,
machine learning, and agent based computational economics.
For a copy of Menczer's PNAS paper, contact him at (319) 335-0884 or firstname.lastname@example.org,
or University News Services at (319) 384-0012 or email@example.com.