6 research outputs found
Improving Customer Relationship Management through Integrated Mining of Heterogeneous Data
The volume of information available on the
Internet and corporate intranets continues to increase along
with the corresponding increase in the data (structured and
unstructured) stored by many organizations. In customer
relationship management, information is the raw material for
decision making. For this to be effective, there is need to
discover knowledge from the seamless integration of structured
and unstructured data for completeness and comprehensiveness
which is the main focus of this paper.
In the integration process, the structured component is
selected based on the resulting keywords from the unstructured
text preprocessing process, and association rules is generated
based on the modified GARW (Generating Association Rules
Based on Weighting Scheme) Algorithm. The main contribution
of this technique is that the unstructured component of the
integration is based on Information retrieval technique which is
based on content similarity of XML (Extensible Markup
Language) document. This similarity is based on the
combination of syntactic and semantic relevance.
Experiments carried out revealed that the extracted
association rules contain important features which form a
worthy platform for making effective decisions as regards
customer relationship management. The performance of the
integration approach is also compared with a similar approach
which uses just syntactic relevance in its information extraction
process to reveal a significant reduction in the large itemsets
and execution time. This leads to reduction in rules generated to
more interesting ones due to the semantic clustering of XML
documents introduced into the improved integrated mining
technique
Los documentos electrónicos : modelización y consulta de documentos estructurados bajo un ambiente orientado a objetos
[Tesis] (Maestría en Informática Administrativa) U.A.N.L.UANLhttp://www.uanl.mx