Literature Digital Library, a Research Index of the NECI. The site was moving to 002-this new place, and It is
now being replaced by new focus of interest like for instance learning, vision
We went there to look for Basic
Knowledge classification hints and volume data
003-Semantic Networks For Conceptual
Analysis, SENECA, from Ernesto García Camarero (email@example.com ), J. García Sanz y M.F.
Verdejo of the Centro de Cálculo, Universidad Complutense de Madrid and
Universidad Politécnica de Madrid, Spain 1980.
We went there to see how to encapsulate knowledge objects.
005-A Survey On Web Information Retrieval Technologies (the document is provided in PDF format), from Lan Huang,
Computer Science Department, State University of New York at Stony Brook,
email: firstname.lastname@example.org, May 1999.
Agents: An Overview,
from Hyacinth S. Nwana from Intelligent Systems
Research, Advanced Applications & Technology Department, BT Laboratories,
Martlesham Heath, Ipswich,
Suffolk, IP5 7RE, U.K.,
went there to see how to perform HK classification made by robots without human
intervention or at least with negligible human intervention in a near future.
Search performance analysis
Done for the following
search engines and directories:
007-Google: to see how the PageRank Algorithm and its Lexicon
008-Altavista: to compare its advanced search facility
performance against Google;
009-Infoseek: to analyze its search among results feature;
015-HITS (published in French),
which stands for Hypertext Induced Topic
Search, created by John Kleinberger, from IBM to identify sources
of authority: We
find very useful to implement the concept of hubs (good sources of links) and
authorities (good sources of content). I think most of our URL's will
correspond to authorities. A good hub is the one that points to many
authorities and conversely a good authority is the one that is pointed to by
We went there to see how to find “good enough” authorities
We went there to see how to implement users’ opinions.
TAPER, which stands for Taxonomy And Path Enhanced Retrieval
system, was developed by 017-Soumen
Chakrabarti, in collaboration with Byron Dom and
Piotr Indyk , from IBM Santa Teresa Research Lab, year 1997.
You may find also the related document (in pdf) Using Taxonomy, Discriminants
and Signatures for navigating in Text Databases, written by Soumen Chakrabarti,
Byron Dom, Rakesh Agrawal and Prabhakar Raghavan of IBM Almaden Research Center, 1997.
018-How do we find
information on the Web by Kiduk Yang,
March29, 2001, School of Information and Library Sciences, University of North
Caroline at Chapel Hill.
019-DBLP Bibliography) is a straightforward and much of common sense procedures
to sample statistically search engines universes.
020-Cybermetrics, with works of Bharat and Broder related to this issue of
measuring the Cyberspace, such us Web mining and Web metrics.
021-Web Archeology, by the Research Group of Compaq where one of the
archeologists is Andrei Broder.
KR - One outstanding IR “authority”
Knowledge Representation by John F. Sowa, August 1999.
We went there to look for systems
thinking concerning our project in three areas: Logic, 022-ontology and
New and Old ideas
Clustering is a
relative “old” technology that once we get one answer to a query it could be
organized in meaningful clusters so if it works and if does not take
significant process time it always add never subtract concerning a better understanding
(no ranking). You may see in action in the new search engine Vivísimo
originated in the Carnegie Mellon University and launched in February 2001. It
works fine in scientific literature, web pages, patent abstracts,
newswires, meeting transcripts, and television transcripts. It is a Meta search engine
because it works over several search engines at a time applying the clustering
process to all the answers. It’s especially apt when users don’t know how to
make accurate queries: they advise to use regular search engines in those
cases. As they work directly on the pipeline of answers, the procedure is
titled “just in time clustering”.
024-Temporal Trends in Document Databases, from
Alexandrin Popescul, Gary William Flake, Steve Lawrence, Lyle H. Ungar, C. Lee
Giles, IEEE Advances in Digital Libraries, ADL 2000, Washington, DC, May 22–24,
pp. 173–182, 2000. To check results they used the Citeseer database available
in 025-Citeseer Index, which
consists of 250,000 articles on Computer Science and they used 150,000. Their
algorithm works on the ideas of co-citation and previously determined
026-Teoma is a project of Computer Labs at Rutgers University
launched on May 2001 trying to excel Google.
We went there to see how to
identify communities and local authorities within.
Basic UK Seeds
027-Collection of Glossaries is another laudable effort made
by Aussie Slang (that’s not a woman but it stands for Australian Slang!) to
facilitate the users’ navigation. It’s only a directory of glossaries and
dictionaries that could be useful to the initial tasks to build the HKM, when
gathering trees, paths and keywords of Major Subjects of the HK (they say have
catalogued more than 3,200 glossaries, really an upper limit to the volume of
028-Towards Knowledge Representation: The State of Data and
Processing Modeling Standards, from Anthony
K. Sarris of Ontek Corporation, 1996: It’s another source to fully depict
the state of the art related to KR. In the Web domain we are dealing with
conventional knowledge, at last forms of the classical written knowledge
complemented with some images.
of Congress site, trying to describe it with words but it will be extremely
difficult to provide a map of its built in knowledge as an institution.
030-ISO, the International Standards
Organization or International Organization for Standardization. We have to
allocate room in the I-URL’s of FIRST to take into consideration that near
We went there to see how it is possible to
represent complex objects like for instance societies and enterprises.
HK Databases models
Digital Library Initiative
Science Foundation (NSF),
The DOD, Department of Defense's 032-Advanced
Research Projects Agency,
And the 033-National
Aeronautics and Space Administration.
Library of Medicine, The Library of Congress
035-National Endowment for the
The FBI, 036-Federal Bureau of