Web community mining and web log mining: commodity cluster based execution

Authors:
Masaru Kitsuregawa;Masashi Toyoda;Iko Pramudiono
Affiliations:
The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan;The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan;The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan
Venue:
ADC '02 Proceedings of the 13th Australasian database conference - Volume 5
Year:
2002

Citing 13
Cited 4

Mining association rules between sets of items in large databases

SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Efficient parallel data mining for association rules

CIKM '95 Proceedings of the fourth international conference on Information and knowledge management
Scalable parallel data mining for association rules

SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Parallel mining algorithms for generalized association rules with classification hierarchy

SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Inferring Web communities from link topology

Proceedings of the ninth ACM conference on Hypertext and hypermedia : links, objects, time and space---structure in hypermedia systems: links, objects, time and space---structure in hypermedia systems
Finding related pages in the World Wide Web

WWW '99 Proceedings of the eighth international conference on World Wide Web
Trawling the Web for emerging cyber-communities

WWW '99 Proceedings of the eighth international conference on World Wide Web
Authoritative sources in a hyperlinked environment

Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
Hash based parallel algorithms for mining association rules

DIS '96 Proceedings of the fourth international conference on on Parallel and distributed information systems
Parallel database processing on a 100 Node PC cluster: cases for decision support query processing and data mining

SC '97 Proceedings of the 1997 ACM/IEEE conference on Supercomputing
Parallel Mining of Association Rules

IEEE Transactions on Knowledge and Data Engineering
Fast Algorithms for Mining Association Rules in Large Databases

VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Mining Generalized Association Rules

VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases

Intelligent web traffic mining and analysis

Journal of Network and Computer Applications - Special issue on computational intelligence on the internet
Human-computer interaction closes the digital divide: a multicultural, intergenerational ICT case study

SEARCC '05 Proceedings of the 2005 South East Asia Regional Computer Science Confederation (SEARCC) Conference - Volume 46
Mining usage profiles from access data using fuzzy clustering

SMO'06 Proceedings of the 6th WSEAS International Conference on Simulation, Modelling and Optimization
Scalable community discovery on textual data with relations

Proceedings of the 17th ACM conference on Information and knowledge management

Quantified Score

Hi-index	0.00

Visualization

Abstract

The emergence of WWW has drawn new frontiers for database research. Web mining has become a hot topic since WWW rapid expansion rate and chaotic nature have exposed some technical challenges as well as interesting discoveries. In general web mining can be classified into web structure mining and web usage mining. Here we introduce two applications of web mining, first from mining the web structure we identify web communities, and the second we mine web usage of mobile internet users on location aware search engine. Those applications require heavy computational power as well as good scalability. Cluster of commodity PCs is suitable as the platform to handle such applications. Here we also report some approaches for optimal parallel execution of mining algorithms on PC cluster.