NDLI: A novel datacube model supporting interactive web-log mining

Content Provider	IEEE Xplore Digital Library
Author	Ohmori, T. Tsutatani, Y. Hoshi, M.
Copyright Year	2002
Description	Author affiliation: Graduate Sch. of Inf. Syst., Univ. of Electro-Commun., Japan (Ohmori, T.; Tsutatani, Y.; Hoshi, M.)
Abstract	Web-log mining is a technique to find "useful" information from access-log data. Typically, association rule mining is used to find frequent patterns (or sequence patterns) of visited pages from access logs and to build users' behavior models from those patterns. In this direction, there exists a difficulty that a human decision-maker must do such data mining process many times under different constraining conditions, different groups of pages, and different levels of abstraction. In order to support this process, this paper proposes a novel datacube model called itemset cube. This cube manages frequent itemsets under various conditions which are modeled by a n-dimensional space. An itemset cube is materialized, sliced, and rolled-up repeatedly in the same way as a traditional scalar datacube is done for interactive scalar-value analysis. Although this looks simple, fast execution of these operations on an itemset cube is difficult. It is because different cells in an itemset cube contain different numbers of records, but these cells must use the same threshold ratios in order to detect frequent itemsets of equal quality. In this paper, a datacube model for storing frequent itemsets is described, and then an efficient algorithm of associated operations is proposed. Its application to a real-life dataset is also demonstrated.
Sponsorship	Hosei Univ
Starting Page	419
Ending Page	427
File Size	1052399
Page Count	9
File Format	PDF
ISBN	0769518621
DOI	10.1109/CW.2002.1180909
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2002-11-06
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Itemsets Data mining Databases Web server Engines Information systems Electronic mail Association rules Humans Time factors
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

A Novel Mining Algorithm for Negative Association Rules

Short Time Association Rule Mining Algorithm

FIAST: A Novel Algorithm for Mining Frequent Itemsets

Novel vertical mining on Diffsets structure

Improving the efficiency of interactive sequential pattern mining by incremental pattern discovery

A Method of Predicting Users' Behaviors Based on Inter-transaction Association Rules

Granule Based Intertransaction Association Rule Mining

Mining Temporal Web Interesting Patterns

An Improved Apriori-based Algorithm for Association Rules Mining

A novel datacube model supporting interactive web-log mining

Similar Documents

A Novel Mining Algorithm for Negative Association Rules

Short Time Association Rule Mining Algorithm

FIAST: A Novel Algorithm for Mining Frequent Itemsets

Novel vertical mining on Diffsets structure

Improving the efficiency of interactive sequential pattern mining by incremental pattern discovery

A Method of Predicting Users' Behaviors Based on Inter-transaction Association Rules

Granule Based Intertransaction Association Rule Mining

Mining Temporal Web Interesting Patterns

An Improved Apriori-based Algorithm for Association Rules Mining

A novel datacube model supporting interactive web-log mining