Paper Info
Title
A Mediator Exploiting Approach for Mining Indirect Associations from Web Data Streams
Abstract
Recently, the concept of indirect associations, a new type of infrequent patterns that indirectly connect two rarely co-occurred items via a frequent item set called 隆搂mediator隆篓, has been shown its power in capturing interesting information over web usage data. Most contemporary indirect association mining algorithms are developed for static dataset. Our previous work has proposed an algorithm, MIA-LM, tailored to streaming data. In this paper, we propose a new efficient algorithm, namely EMIA-LM, for mining indirect associations over web data streams. EMIA-LM employs a mediator-exploiting search strategy, which reduce the search space as well as computation cost for generating indirect associations. Besides, EMIA-LM adopts a compact data structure, alleviating unnecessary data transforming processes and consuming far less memory storage. Preliminary experiments conducted on real Web streaming datasets show that EMIA-LM is superior to the leading HI-mine* algorithm for static data and MIA-LM both in computation speed and memory consumption.
Year
DOI
Venue
2011
10.1109/IBICA.2011.50
IBICA
Keywords
Field
DocType
new efficient algorithm,computation speed,computation cost,static data,web data streams,contemporary indirect association mining,web usage data,compact data structure,unnecessary data,mining indirect associations,mediator exploiting approach,indirect association,web data stream,data structures,data structure,data transformation,memory management,data model,heuristic algorithm,internet,data mining,mediator,data models,algorithm design and analysis,search space
Data structure,Data mining,Data modeling,Data stream mining,Algorithm design,Computer science,Data stream,Memory management,The Internet,Computation
Conference
Citations 
PageRank 
References 
2
0.36
8
Authors
2
Name
Order
Citations
PageRank
Wen-Yang Lin139935.72
Yi-Ching Chen21026.67