Campus Units

Electrical and Computer Engineering

Document Type

Conference Proceeding

Conference

8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2016)

Publication Version

Published Version

Publication Date

2016

Journal or Book Title

Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2016)

Volume

1

First Page

456

Last Page

462

DOI

10.5220/0006092104560462

Conference Title

8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2016)

Conference Date

November 9-11, 2016

City

Porto, Portugal

Abstract

We develop and design a novel clustering algorithm to capture utility information in transactional data. Transactional data is a special type of categorical data where transactions can be of varying length. A key objective for all categorical data analysis is pattern recognition. Therefore, transactional clustering algorithms focus on capturing the information on high frequency patterns from the data in the clusters. In recent times, utility information for category types in the data has been added to the transactional data model for a more realistic representation of data. As a result, the key information of interest has become high utility patterns instead of high frequency patterns. To the best our knowledge, no existing clustering algorithm for transactional data captures the utility information in the clusters found. Along with our new clustering rationale we also develop corresponding metrics for evaluating quality of clusters found. Experiments on real datasets show that the clusters found by our algorithm successfully capture the high utility patterns in the data. Comparative experiments with other clustering algorithms further illustrate the effectiveness of our algorithm.

Comments

This proceeding is published as Lakhawat, P., Mishra, M. and Somani, A. "A Novel Clustering Algorithm to Capture Utility Information in Transactional Data." In Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2016) - Volume 1: KDIR, 456-462, 2016, Porto, Portugal. DOI: 10.5220/0006092104560462. Published in SCITEPRESS Digital Library. Posted with permission.

Copyright Owner

SCITEPRESS – Science and Technology Publications, Lda

Language

en

File Format

application/pdf

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