Authors:
Cristina Wanzeller
1
and
Orlando Belo
2
Affiliations:
1
Escola Superior de Tecnologia, Instituto Politécnico de Viseu, Portugal
;
2
Escola de Engenharia, Universidade do Minho, Portugal
Keyword(s):
Web usage mining, clickstream data mining assistance, case based reasoning and similarity measures.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Biomedical Engineering
;
Business Analytics
;
Case-Based Reasoning
;
Data Engineering
;
Data Mining
;
Databases and Information Systems Integration
;
Datamining
;
Enterprise Information Systems
;
Health Information Systems
;
Pattern Recognition
;
Sensor Networks
;
Signal Processing
;
Soft Computing
;
Symbolic Systems
;
Theory and Methods
Abstract:
We implemented a mining plans selection system founded on the Case Based Reasoning paradigm, in order to assist the development of Web usage mining processes. The system’s main goal is to suggest the most suited methods to apply on a data analysis problem. Our approach builds upon the reuse of the experience gained from prior successfully mining processes, to solve current and future similar problems. The knowledge acquired after successfully solving such problems is organized and stored in a relational case base, giving rise to a (multi-) relational cases representation. In this paper we describe the similitude assessment devised within the retrieval of similar cases, to cope with the adopted representation. Structured representation and similarity assessment over complex data are issues relevant to a growing variety of application domains, being considered in multiple related lines of active research. We explore a number of different similarity measures proposed in the literature a
nd we extend one of them to better fit our purposes.
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