NDLI: Rule-Chain Incremental Mining Algorithm Based on Directed Graph

Content Provider	IEEE Xplore Digital Library
Author	Hongyun Ning Zhiying Zhang Degan Zhang
Copyright Year	2009
Abstract	Aiming to discover the rule-chains directly, a novel graph-based online incremental mining algorithm (RIOMining) is proposed. Firstly, an interrelated bitmap based on a directed graph (PAGraph) is designed to compress the rule-chain information for storage. The compressed storage of the directed-graph effectively avoids repetitious database scanning and makes meaningful rules found more conveniently. Secondly, four theorems about discovery and pruning of frequent path in the graph are proved, so as to the rule-chains could be iteratively generated by searching incremental paths, while the theorems narrow the search scope and promote the performance by properly pruning and extending paths. It effectively reduces the redundancy calculation. Comparing it with other two fast mining algorithms, DLG and FP-growth, experimental result shows that it can mine rule-chains of high quality, especially, it is of real-time accuracy, and thereby it can be widely applied to dynamic network environment.
Starting Page	118
Ending Page	122
File Size	380911
Page Count	5
File Format	PDF
ISBN	9780769537351
DOI	10.1109/FSKD.2009.587
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-08-14
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Incremental Mining Computer vision Laboratories Association rule Educational technology Transaction databases Data mining Association rules Iterative algorithms Computer science education Fuzzy systems Rule-chain Frequent Path Discovery
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

Incremental association rule mining using promising frequent itemset algorithm

Incremental update for fuzzy association rules

Self-optimization Rule-chain Mining Based on Potential Association Rule Directed Graph

An Incremental Updating Algorithm for Online Mining Association Rules

Mining Direct and Indirect Weighted Fuzzy Association Rules in Large Transaction Databases

Research on a Graph-Based Algorithm

A new technique for fast frequent closed itemsets mining

A New Parallel Algorithm for the Frequent Itemset Mining Problem

Parallel algorithm for mining fuzzy association rules

Rule-Chain Incremental Mining Algorithm Based on Directed Graph

Similar Documents

Incremental association rule mining using promising frequent itemset algorithm

Incremental update for fuzzy association rules

Self-optimization Rule-chain Mining Based on Potential Association Rule Directed Graph

An Incremental Updating Algorithm for Online Mining Association Rules

Mining Direct and Indirect Weighted Fuzzy Association Rules in Large Transaction Databases

Research on a Graph-Based Algorithm

A new technique for fast frequent closed itemsets mining

A New Parallel Algorithm for the Frequent Itemset Mining Problem

Parallel algorithm for mining fuzzy association rules

Rule-Chain Incremental Mining Algorithm Based on Directed Graph