Article

A data mining based system supporting tactical decisions

Authors:

Giuseppe Polese,

Massimiliano Troiano,

Genoveffa TortoraAuthors Info & Claims

SEKE '02: Proceedings of the 14th international conference on Software engineering and knowledge engineering

Pages 681 - 684

https://doi.org/10.1145/568760.568877

Published: 15 July 2002 Publication History

Get Access

Abstract

We present a decision support system based on data mining algorithms to be used for tactical decisions. The system has been developed and engineered to solve a typical problem involving strategic decisions: supporting a trainer of a basketball team in making technical/tactical decisions. The experiments conducted on this application domain proved the effectiveness of the system and its underlying algorithms. The basketball domain stressed several aspects of decision making, proving that the used approach is suitable for other domains involving tactical decisions.

References

[1]

Adriaans P., Zantinge D., "Data Mining", Addison-Wesley, 1996.

Digital Library

Google Scholar

[2]

Agrawal R. and Srikant R., "Fast Algorithms for Mining Association Rules in Large Databases", in Proceedings of VLDB 1994.

Digital Library

Google Scholar

[3]

Agrawal R., Imielinski T., Swami A., "Mining Association Rules Between Sets of Items in Large Databases", in Proceedings of the ACM SIGMOD Conference on Management of Data, Washington, D.C., May 1993, pp. 207-216.

Digital Library

Google Scholar

[4]

Chen M., Han J., Yu P. S., "Data Mining: An Overview from a Database Perspective",IEEE TKDE, 8:6, December 1996.

Digital Library

Google Scholar

[5]

Troiano M., "An Intelligent System to Support Decisions of a Basketball Trainer based on the Apriori Data Mining Algorithm", Master Thesis, University of Salerno, Italy, 2000.

Google Scholar

[6]

Ventre A., "An Intelligent System to Support Decisions of a Basketball Trainer: TheDecision Query Verification Module", Master Thesis, University of Salerno, Italy, 2000

Google Scholar

Cited By

View all

Harikrishnan VDeore HRaju PAgrawal ASharma M(2021)Predictive Analysis Using Machine Learning Techniques for Fantasy GamesAdvances in Mechanical Engineering10.1007/978-981-16-0942-8_65(683-692)Online publication date: 27-Jun-2021
https://doi.org/10.1007/978-981-16-0942-8_65
Lam M(2017)TLGProb: Two-Layer Gaussian Process Regression Model for Winning Probability Calculation in Two-Team SportsArtificial Intelligence and Soft Computing10.1007/978-3-319-59060-8_26(280-291)Online publication date: 24-May-2017
https://doi.org/10.1007/978-3-319-59060-8_26
Zheng HCheung GFang L(2015)Analysis of sports statistics via graph-signal smoothness prior2015 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)10.1109/APSIPA.2015.7415436(1071-1076)Online publication date: Dec-2015
https://doi.org/10.1109/APSIPA.2015.7415436
Show More Cited By

A data mining based system supporting tactical decisions
1. Information systems
  1. Information systems applications

Recommendations

Bridging the gap between data mining and decision support: A case-based reasoning and ontology approach
Philosophies and Methodologies for Knowledge Discovery

Nowadays, decision makers invariably need to use decision support technology (DS) such as data mining (DM) methodologies and tools in order to tackle complex decision making problems. However the successful application of DM technology requires that one ...
The Study on the Application of Data Mining Based on Association Rules
CSNT '12: Proceedings of the 2012 International Conference on Communication Systems and Network Technologies

Association rule mining finds interesting association or correlation relationships among a large set of data items, which is an important task of data mining. Meanwhile, Apriori is an influential algorithm for mining frequent itemsets for Boolean ...
Improving Decision Making by Means of a Marketing Decision Support System

Marketing decision makers are confronted with an increasing amount of information. This leads to a complex decision environment that may cause decision makers to lapse into using mental-effort-reducing heuristics such as anchoring and adjustment. In an ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

SEKE '02: Proceedings of the 14th international conference on Software engineering and knowledge engineering

July 2002

859 pages

ISBN:1581135564

DOI:10.1145/568760

Conference Chairs:
Genny Tortora,
Shi-Kuo Chang

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 15 July 2002

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Article

Conference

SEKE02

SEKE02: 14th International Conference on Software Engineering and Knowledge Engineering

July 15 - 19, 2002

Ischia, Italy

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

4
Total Citations
View Citations
1,191
Total Downloads

Downloads (Last 12 months)4
Downloads (Last 6 weeks)2

Reflects downloads up to 13 Dec 2024

Other Metrics

View Author Metrics

Citations

Cited By

View all

Harikrishnan VDeore HRaju PAgrawal ASharma M(2021)Predictive Analysis Using Machine Learning Techniques for Fantasy GamesAdvances in Mechanical Engineering10.1007/978-981-16-0942-8_65(683-692)Online publication date: 27-Jun-2021
https://doi.org/10.1007/978-981-16-0942-8_65
Lam M(2017)TLGProb: Two-Layer Gaussian Process Regression Model for Winning Probability Calculation in Two-Team SportsArtificial Intelligence and Soft Computing10.1007/978-3-319-59060-8_26(280-291)Online publication date: 24-May-2017
https://doi.org/10.1007/978-3-319-59060-8_26
Zheng HCheung GFang L(2015)Analysis of sports statistics via graph-signal smoothness prior2015 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)10.1109/APSIPA.2015.7415436(1071-1076)Online publication date: Dec-2015
https://doi.org/10.1109/APSIPA.2015.7415436
Miljkovic DGajic LKovacevic AKonjovic Z(2010)The use of data mining for basketball matches outcomes predictionIEEE 8th International Symposium on Intelligent Systems and Informatics10.1109/SISY.2010.5647440(309-312)Online publication date: Sep-2010
https://doi.org/10.1109/SISY.2010.5647440

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Cited By

Recommendations

Bridging the gap between data mining and decision support: A case-based reasoning and ontology approach

The Study on the Application of Data Mining Based on Association Rules

Improving Decision Making by Means of a Marketing Decision Support System