ACM Home Page
Please provide us with feedback. Feedback
Winnowing-based text clustering
Full text PdfPdf (163 KB)
Source
Conference on Information and Knowledge Management archive
Proceeding of the 17th ACM conference on Information and knowledge management table of contents
Napa Valley, California, USA
POSTER SESSION: Poster session 1/information retrieval table of contents
Pages 1353-1354  
Year of Publication: 2008
ISBN:978-1-59593-991-3
Authors
Javier Parapar  University of A Coruña, A Coruña, Spain
Álvaro Barreiro  University of A Coruña, A Coruña, Spain
Sponsors
ACM: Association for Computing Machinery
SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web
SIGIR: ACM Special Interest Group on Information Retrieval
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 5,   Downloads (12 Months): 82,   Citation Count: 0
Additional Information:

abstract   references   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/10.1145/1458082.1458275
What is a DOI?

ABSTRACT

We present an approach to document clustering based on winnowing fingerprints that achieved good values of effectiveness with considerable save in memory space and computation time.


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
2
3
4
 
5
M. Rosell, V. Kann, and J.-E. Litton. Comparing comparisons: Document clustering evaluation using two manual classications. In ICON'04, 2004.
6
 
7
F. Giannotti and C. Gozzi. Characterizing web user accesses: A transactional approach to web log clustering in ITCC '02, pages 312--317, 2002.

Collaborative Colleagues:
Javier Parapar: colleagues
Álvaro Barreiro: colleagues