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Authors: Piyush Lakhawat ; Mayank Mishra and Arun Somani

Affiliation: Iowa State University, United States

Keyword(s): High Utility Itemset Mining, Clustering, Itemset Prediction.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; BioInformatics & Pattern Discovery ; Data Mining in Electronic Commerce ; Information Extraction ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Mining Text and Semi-Structured Data ; Symbolic Systems ; User Profiling and Recommender Systems

Abstract: We strongly believe that the current Utility Itemset Mining (UIM) problem model can be extended with a key modeling capability of predicting future itemsets based on prior knowledge of clusters in the dataset. Information in transactions fairly representative of a cluster type is more a characteristic of the cluster type than the the entire data. Subjecting such transactions to the common threshold in the UIM problem leads to information loss. We identify that an implicit use of the cluster structure of data in the UIM problem model will address this limitation. We achieve this by introducing a new clustering based utility in the definition of the UIM problem model and modifying the definitions of absolute utilities based on it. This enhances the UIM model by including a predictive aspect to it, thereby enabling the cluster specific patterns to emerge while still mining the inter-cluster patterns. By performing experiments on two real data sets we are able to verify that our proposed predictive UIM problem model extracts more useful information than the current UIM model with high accuracy. (More)

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Paper citation in several formats:
Lakhawat, P.; Mishra, M. and Somani, A. (2017). A Clustering based Prediction Scheme for High Utility Itemsets. In Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2017) - KDIR; ISBN 978-989-758-271-4; ISSN 2184-3228, SciTePress, pages 123-134. DOI: 10.5220/0006590001230134

@conference{kdir17,
author={Piyush Lakhawat. and Mayank Mishra. and Arun Somani.},
title={A Clustering based Prediction Scheme for High Utility Itemsets},
booktitle={Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2017) - KDIR},
year={2017},
pages={123-134},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006590001230134},
isbn={978-989-758-271-4},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2017) - KDIR
TI - A Clustering based Prediction Scheme for High Utility Itemsets
SN - 978-989-758-271-4
IS - 2184-3228
AU - Lakhawat, P.
AU - Mishra, M.
AU - Somani, A.
PY - 2017
SP - 123
EP - 134
DO - 10.5220/0006590001230134
PB - SciTePress

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