Re: DM: Web Data Mining

[David L Dowe]

   Dear Devanshu,

      The papers below might be of interest.

David.

Dr. David Dowe, Senior Lecturer, School of Computer Science and 
Software Eng.,
Monash University, Clayton, Victoria 3168, Australia     
dld@cs.monash.edu.au
Tel:+61 3 9905-5776  Fax:+61 3 9905-5146   
http://www.csse.monash.edu.au/~dld/


D L Dowe, L Allison and G Pringle (1998).  The hunter and the hunted -
      modelling the relationship between Web pages and search engines,
      pp380-382, 2nd Pacific-Asia Conference on Knowledge Discovery 
and Data
      Mining (PAKDD98), Lecture Notes in Artificial Intelligence 
(LNAI) 1394,
      Melbourne, Australia, April 1998

G Pringle, L Allison and D L Dowe (1998).  What is a tall poppy among 
Web
      pages?, in H Ashman and P Thistlewaite (eds.), Computer 
Networks and ISDN
      Systems (Journal): Proceedings of the 7th International World 
Wide Web
      Conference, Brisbane, Australia, 14-18 April 1998, Elsevier 
Science BV,
      Netherlands, ISBN: 0169-7552-98, Vol. 30: 1-7: pp369-377

> From owner-datamine-l@nessie.crosslink.net  Tue Dec  1 03:36:18 1998
> From: #DEVANSHU DHYANI# <SA1377897@ntu.edu.sg>
> To: "'datamine-l@nautilus-sys.com'" <datamine-l@nautilus-sys.com>
> Subject: DM: Web Data Mining
> Date: Mon, 30 Nov 1998 23:37:01 +0800
> 
> I am involved in research aimed towards extending the utility of 
>data mining
> to semi-structured data such as WWW documents. In applying standard 
>KDD
> operators such as discovering association and characteristic rules,
> classification, clustering to generalization based mining on an 
>information
> base derived from WWW documents we are faced with the following 
>questions:
> 
> 1. The information base itself must support storage, retrieval and 
>querying
> operations on semi-sturctured data. In our search for an 
>appropriate data
> model we have come across the XML/DOM (anticipated as the heir to 
>HTML, as
> markup for web docuemnts) and the somewhat similar Lore DBMS(by the 
>Stanford
> Database group). Are there any other suitable data models that are
> appropriate for mining related tasks on semi-sturctured data?
> 
> 2. Generalization based data-mining prerequisites the availability 
>of domain
> specific background knowledge. Although the use of concept 
>hierarchies
> fulfils this requirement by aiding attribute oriented induction and 
>concept
> tree ascension (in relational databases), their disadvantage lies 
>in the
> need to generate them manually for each domain. We are exploring the
> possibility of adapting pre-existing, shared, reusable ontologies 
>(such as
> those in the Ontolingua system under the DARPA Knowlege Sharing 
>effort) for
> this purpose. Would the use of available ontologies improve the
> generalization process especially because these may cover greater 
>domain
> knowledge (both in depth and extent of concepts) than indegineous 
>concept
> hierarchies?
> 
>    Thanks for your help.
> 
> Devanshu Dhyani
> Undergraduate student,
> Centre for Advanced Information Systems (CAIS),
> Nanyang Technological University,
> Singapore.