DRO

An incremental FP-growth web content mining and its application in preference identification

Hang, Xiaoshu, Liu, James N.K., Ren, Yu and Dai, Honghua 2005, An incremental FP-growth web content mining and its application in preference identification, Lecture notes in computer science, vol. 3683, pp. 121-127.

Attached Files
Name Description MIMEType Size Downloads

Title An incremental FP-growth web content mining and its application in preference identification
Author(s) Hang, Xiaoshu
Liu, James N.K.
Ren, Yu
Dai, Honghua
Journal name Lecture notes in computer science
Volume number 3683
Start page 121
End page 127
Publisher Springer-Verlag
Place of publication Berlin, Germany
Publication date 2005
ISSN 0302-9743
1611-3349
Keyword(s) intelligent e-mail analysis
news extraction
web mining
Summary This paper presents a real application of Web-content mining using an incremental FP-Growth approach. We firstly restructure the semi-structured data retrieved from the web pages of Chinese car market to fit into the local database, and then employ an incremental algorithm to discover the association rules for the identification of car preference. To find more general regularities, a method of attribute-oriented induction is also utilized to find customer’s consumption preferences. Experimental results show some interesting consumption preference patterns that may be beneficial for the government in making policy to encourage and guide car consumption.
Notes Book Title : Knowledge-Based Intelligent Information and Engineering Systems
Language eng
Field of Research 080199 Artificial Intelligence and Image Processing not elsewhere classified
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2005, Springer-Verlag Berlin Heidelberg
Persistent URL http://hdl.handle.net/10536/DRO/DU:30003318

Document type: Journal Article
Collection: School of Information Technology
Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Versions
Version Filter Type
Access Statistics: 433 Abstract Views, 0 File Downloads  -  Detailed Statistics
Created: Mon, 07 Jul 2008, 08:49:40 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.