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Author: Tapio Pitkaranta

Affiliation: Helsinki University of Technology, Finland

Keyword(s): Information retrieval, Similarity search, Coded data sets, Nearest neighbor, Kernel functions

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Business Analytics ; Coupling and Integrating Heterogeneous Data Sources ; Data Engineering ; Data Mining ; Data Warehouses and OLAP ; Databases and Information Systems Integration ; Datamining ; Enterprise Information Systems ; Health Information Systems ; Sensor Networks ; Signal Processing ; Soft Computing

Abstract: Coded data sets form the basis for many well known applications from healthcare prospective payment system to recommender systems in online shopping. Previous studies on coded data sets have introduced methods for the analysis of rather small data sets. This study proposes applying information retrieval methods for enabling high performance analysis of data masses that scale beyond traditional approaches. An essential component in today’s data warehouses to which coded data sets are collected is a database management system (DBMS). This study presents experimental results how information retrieval indexes scale and outperform common database schemas with a leading commercial DBMS engine in analysis of coded data sets. The results show that flexible analysis of hundreds of millions of coded data sets is possible with a regular desktop hardware.

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Paper citation in several formats:
Pitkaranta, T. (2009). APPLYING INFORMATION RETRIEVAL FOR MARKET BASKET RECOMMENDER SYSTEMS. In Proceedings of the 11th International Conference on Enterprise Information Systems - Volume 3: ICEIS; ISBN 978-989-8111-84-5; ISSN 2184-4992, SciTePress, pages 138-143. DOI: 10.5220/0001991101380143

@conference{iceis09,
author={Tapio Pitkaranta.},
title={APPLYING INFORMATION RETRIEVAL FOR MARKET BASKET RECOMMENDER SYSTEMS},
booktitle={Proceedings of the 11th International Conference on Enterprise Information Systems - Volume 3: ICEIS},
year={2009},
pages={138-143},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001991101380143},
isbn={978-989-8111-84-5},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 11th International Conference on Enterprise Information Systems - Volume 3: ICEIS
TI - APPLYING INFORMATION RETRIEVAL FOR MARKET BASKET RECOMMENDER SYSTEMS
SN - 978-989-8111-84-5
IS - 2184-4992
AU - Pitkaranta, T.
PY - 2009
SP - 138
EP - 143
DO - 10.5220/0001991101380143
PB - SciTePress