Hierarchical Pattern-Based Clustering for Grouping Web Transactions

Abstract:
Grouping customer transactions into segments is important in order to obtain better understanding of customers pattern. Currently, the hierarchical pattern-based clustering has been used to group customer transactions into segments. However, the processing time is still high due to difference parameter used between two clusters. In this paper, the difference will be based on the different between the summations of each c ....etc

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To get full information or details of hierarchical clustering please have a look on the pages

http://seminarsprojects.net/Thread-efficient-clustering-scheme-to-exploit-hierarchical-data-in-network-traffic-analysis

http://seminarsprojects.net/Thread-ontology-discovery-for-the-semantic-web-using-hierarchical-clustering

if you again feel trouble on hierarchical clustering please reply in that page and ask specific fields in hierarchical clustering ....etc

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uml diagrams for a framework for personal mobile commerce pattern mining and prediction ....etc

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Grouping Technique for Cooperative Spectrum Sensing in Cognitive Radios

Rizwan Akhtar, Adnan Rashdi and Abdul Ghafoor
Electrical Engineering Department, College of Signals, National University of Science & Technology, Pakistan


Abstract

Cognitive networks can potentially solve the
problems of spectrum scarcity by accommodating unlicensed
(secondary) users in under-utilized segments of the spectrum.
Spectrum sensing serves as the primary stimulus for a cognitive
radio and is vitally impor ....etc

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variables (e.g., customer loyalty) and on using cluster analysis and mixture models for segmentation. The data mining literature has provided various clustering algorithms for segmentation without focusing specifically on clustering customer transactions. Building on the notion that observable customer transactions are generated by latent behavioral traits, in this paper, we investigate using a pattern-based clustering approach to grouping customer transactions. We define an objective function that we maximize in order to achieve a good cluster ....etc

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Report and ppt for validation of mining association rules with hierarchical clustering ....etc

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ABSTRACT
This paper proposes a new multimedia ontology based scheme for semantic multimedia data processing on the web. The ontology language Multimedia Web Ontology Language (MOWL), is designed as an extension of OWL, the W3C recommended ontology language for the web. MOWL supports creation of and reasoning with perceptual modeling of concepts, and probabilistic evidential reasoning. Ontologies and context logic are closely related. Each context is ontology, and ontology inclusion could be one particular type of l ....etc

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GHIC: A Hierarchical Pattern-based Clustering Algorithm for Grouping Web Transactions
IEE Transactions on Knowledge and Data Engineering, Vol. 17, No. 9, Language: Java

Abstract: Grouping customer transactions into segments may help understand customers better. The marketing literature has concentrated on identifying important segmentation variables (e.g., customer loyalty) and on using cluster analysis and mixture models for segmentation. The data mining literature has provided various clustering algorithms for segmentation without focusin ....etc

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To get full information or details of hierarchical clustering please have a look on the pages

http://seminarsprojects.net/Thread-efficient-clustering-scheme-to-exploit-hierarchical-data-in-network-traffic-analysis

http://seminarsprojects.net/Thread-ontology-discovery-for-the-semantic-web-using-hierarchical-clustering

if you again feel trouble on hierarchical clustering please reply in that page and ask specific fields in hierarchical clustering ....etc

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can i have all uml diagrams for Effective Pattern Discovery for Text Mining.
Abstract
Many data mining techniques have been proposed for mining useful patterns in text documents. However, how to effectively use and update discovered patterns is still an open research issue, especially in the domain of text mining. Since most existing text mining methods adopted term-based approaches, they all suffer from the problems of polysemy and synonymy. Over the years, people have often held the hypoth ....etc

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