ACM Home Page
Please provide us with feedback. Feedback
Digital Library logoTake a look at the new version of this page: [ beta version ]. Tell us what you think.
Collection synthesis
Full text PdfPdf (322 KB)
Source International Conference on Digital Libraries archive
Proceedings of the 2nd ACM/IEEE-CS joint conference on Digital libraries table of contents
Portland, Oregon, USA
SESSION: Models and tools for generating digital libraries table of contents
Pages: 253 - 262  
Year of Publication: 2002
ISBN:1-58113-513-0
Author
Donna Bergmark  Cornell Digital Library Research Group, Ithaca, NY
Sponsor
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 2,   Downloads (12 Months): 58,   Citation Count: 12
Additional Information:

abstract   references   cited by   index terms   collaborative colleagues  

Tools and Actions: Request Permissions Request Permissions    Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/544220.544275
What is a DOI?

ABSTRACT

The invention of the hyperlink and the HTTP transmission protocol caused an amazing new structure to appear on the Internet -- the World Wide Web. With the Web, there came spiders, robots, and Web crawlers, which go from one link to the next checking Web health, ferreting out information and resources, and imposing organization on the huge collection of information (and dross) residing on the net. This paper reports on the use of one such crawler to synthesize document collections on various topics in science, mathematics, engineering and technology. Such collections could be part of a digital library.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
W. Arms. Automated digital libraries: How effectively can computers be used for the skill tasks of professional librarianship. D-Lib Magazine: The Magazine of Digital Library Research, July 2000. http://www.dlib.org/dlib/july00/arms/07arms.html
2
 
3
R. K. Belew. Finding Out About. Cambridge Press, 2001
 
4
5
 
6
C. M. Bowman, P. B. Danzig, D. R. Hardy, U. Manber, and M. F. Schwartz. Harvest: A scalable, customizable discovery and access system. Technical Report CU-CS-732-94, Department of Computer Science, University of Colorado, Boulder, July 1994
 
7
C. M. Bowman, P. B. Danzig, D. R. Hardy, U. Manber, and M. F. Schwartz. The Harvest information discovery and access system, 1994. Additional information available http://archive.ncsa.uiuc.edu/SDG/IT94/Proceedings/Searching/schwartz.harvest/schwartz.harvest.html
 
8
 
9
A. Broder, S. Glassman, and M. Manasse. Clustering the Web, 1999. Available: http://www.research.compaq.com/SRC/articles/199707/cluster.html
 
10
 
11
12
 
13
 
14
S. Chakrabarti, B. E. Dom, D. Gibson, R. Kumar, P. Raghavan, S. Rajagopalan, and A. Tomkins. Experiments in topic distillation. In Proceedings of the ACM SIGIR Workshop on Hypertext Information Retrieval on the Web, Melbourne, Australia, 1998. ACM. Available: http://www.almaden.ibm.com/cs/k53/abstract.html
 
15
 
16
C. Chekuri, M. Goldwasser, P. Raghavan, and E. Upfal. Web search using automatic classification, 1997. Available at http://cm.bell-labs.com/who/chekuri/postscript/web.ps.gz Current as of December 5, 2001
 
17
18
 
19
 
20
 
21
E. Garfield. Mapping the structure of science, pages 98--147. John Wiley & Sons, Inc. NY, 1979. Available at http://www.garfield.library.upenn.edu/ci/chapter8.pdf
22
 
23
E.-H. S. Han and G. Karypis. Centroid-based document classification: Analysis & experimental results. Technical Report 00-017, Computer Science, University of Minnesota, Mar. 2000
 
24
T. H. Haveliwala, A. Gionis, and P. Indyk. Scalable techniques for clustering the Web. In WebDB'2000: Third International Workshop on the Web and Databases, May 2000. Available http://www.research.att.com/conf/webdb2000/PAPERS/8c.ps
 
25
 
26
 
27
28
29
 
30
S. Lawrence and C. L. Giles. Accessibility of information on the Web. Nature, 400(8), July 1999
31
 
32
 
33
F. Menczer and R. K. Belew. Adaptive Retrieval Agents: Internalizing Local Context and Scaling up to the Web, pages 1--45. 1999
34
 
35
 
36
 
37
M. Najork and A. Heydon. High-performance Web crawling. Technical Report Research Report 173, Compaq SRC, Sept. 2001. Available at http://gatekeeper.research.compaq.com/pub/DEC/SRC/research-reports/abstracts/src-rr-173.html
38
 
39
 
40
B. Saulnier. Portal power. Cornell Engineering Magazine, pages 16--21, Fall 2001. Available:http://www.engineering.cornell.edu/engrMagazine/
 
41
 
42
D. Voss. Better searching through science. Science, 293(5537):2024, 2001. Available: http://www.sciencemag.org/cgi/content/full/293/5537/2024
 
43
44
45
46
 
47
L. L. Zia. The NSF national science, technology, engineering, and mathematics education digital library (NSDL) program: New projects and a project report. D-Lib Magazine: The Magazine of Digital Library Research, 7(11), Nov. 2001

CITED BY  12