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A model for fast web mining prototyping
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Source Web Search and Web Data Mining archive
Proceedings of the Second ACM International Conference on Web Search and Data Mining table of contents
Barcelona, Spain
SESSION: Web mining I table of contents
Pages 114-123  
Year of Publication: 2009
ISBN:978-1-60558-390-7
Authors
Álvaro Pereira  Federal Univ. of Minas Gerais, Belo Horizonte, Brazil
Ricardo Baeza-Yates  Yahoo! Research & Barcelona Media, Barcelona, Spain
Nivio Ziviani  Federal Univ. of Minas Gerais, Belo Horizonte, Brazil
Jesús Bisbal  Universitat Pompeu Fabra, Barcelona, Spain
Sponsors
SIGMOD: ACM Special Interest Group on Management of Data
: Google
SIGIR: ACM Special Interest Group on Information Retrieval
SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web
: Yahoo! Research
Microsoft : Microsoft
: Nokia
SIGKDD: ACM Special Interest Group on Knowledge Discovery in Data
Publisher
ACM  New York, NY, USA
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ABSTRACT

Web mining is a computation intensive task, even after the mining tool itself has been developed. Most mining software are developed ad-hoc and usually are not scalable nor reused for other mining tasks. The objective of this paper is to present a model for fast Web mining prototyping, referred to as WIM -- Web Information Mining. The underlying conceptual model of WIM provides its users with a level of abstraction appropriate for prototyping and experimentation throughout the Web data mining task. Abstracting from the idiosyncrasies of raw Web data representations facilitates the inherently iterative mining process. We present the WIM conceptual model, its associated algebra, and the WIM tool software architecture, which implements the WIM model. We also illustrate how the model can be applied to real Web data mining tasks. The experimentation of WIM in real use cases has shown to significantly facilitate Web mining prototyping.


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.

 
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D. Borthakur. The hadoop distributed file system: Architecture and design, 2007. http://hadoop.apache.org/core/docs/current/hdfs_design.pdf.
 
5
 
6
DB2 Intelligent Miner, July 2008. http://www-306.ibm.com/software/data/iminer/.
7
8
 
9
Hadoop, July 2008. http://hadoop.apache.org/.
10
 
11
 
12
A. O. Mendelzon, G. A. Mihaila, and T. Milo. Querying the World Wide Web. Intl. Journal on Digital Libraries, 1(1):54--67, 1997.
 
13
Microsoft SQL Server 2005 Data Mining, July 2008. http://www.microsoft.com/sql/technologies/dm.
 
14
 
15
Oracle Data Mining, July 2008. http://www.oracle.com/technology/products/bi/odm.
 
16
A. Pereira, R. Baeza-Yates, and N. Ziviani. A model for web mining applications -- conceptual model, architecture, implementation and use cases. Technical Report 001/2008, Federal Univ. of Minas Gerais, Feb. 2008. http://www.dcc.ufmg.br/~alvaro/pbz08b.pdf.
 
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Collaborative Colleagues:
Álvaro Pereira: colleagues
Ricardo Baeza-Yates: colleagues
Nivio Ziviani: colleagues
Jesús Bisbal: colleagues