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, doi: 10.1007/11553939_18. 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 DOI 10.1007/11553939_18 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 Related Links Link Description Connect to published version (restricted access) Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Tue, 06 Jan 2009, 13:18:46 EST Wed, 15 Feb 2012, 14:57:19 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 0 times in Scopus Search Google Scholar Access Statistics: 583 Abstract Views, 0 File Downloads  -  Detailed Statistics Created: Mon, 07 Jul 2008, 08:49:40 EST

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