An intelligent framework (O-SS-E) for data mining, knowledge discovery and business intelligence

Proceedings - International Workshop on Database and Expert Systems Applications, DEXA

Volumn 2006, Issue , 2005, Pages 715-719

  Rennolls, Keith ^a  

^a UNIVERSITY OF GREENWICH   (United Kingdom)

Author keywords

Business Intelligence; Data Mining; Epistemology; ERA; Knowledge Discovery; Meaning; Ontology; Sampling; Search; Semantics

Indexed keywords

BUSINESS-INTELLIGENCE; EPISTEMOLOGY; ERA; KNOWLEDGE DISCOVERY; ONTOLOGY;

COMPETITIVE INTELLIGENCE; DATA MINING; DATA WAREHOUSES; DECISION SUPPORT SYSTEMS; INFORMATION RETRIEVAL; MATHEMATICAL MODELS; SAMPLING; SEMANTICS;

INTELLIGENT AGENTS;

EID: 33749045680     PISSN: 15294188     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/DEXA.2005.48     Document Type: Conference Paper

References (16)

1. Ayer, A.J. (1973) The Central Questions of Philosophy. Weidenfeld and Nicolson. London, p.58.
2. Berners-Lee, T. (1998) Semantic Web Road Map, September 1998. http://www.w3.org/DesignIssues/Semantic.html
3. Chaudhuri, S., Das, G., Datar, M., Motwani, R. and Narasayya, V. (2001) Overcoming Limitations of Sampling for Aggregation Queries. Proc. IEEE Conf. on Data Engineering.
4. Chaudhuri, S., Motwani, R. and Narasayya, V. (1999) On Random Sampling over Joins. Proc of ACM SIGMOD Int. Conf. on Man. of Data. pp263-274.
5. Chaudhuri, S., Motwani, R. and Narasayya, V. (1998) Using Random Sampling for Histogram Construction. Proc. ACM SIGMOD Conf. pp436-447.
6. CLEMENTINE (2005) http://www.spss.com/clementine/
7. Codd, E. F. (1970) A Relational Model of Data for Large Shared Data Banks. Communications of the ACM, Vol. 13, No. 6, June 1970, pp. 377-387.
8. Codd, E. F. (1979) Extending the Data Base Relational Model to Capture More Meaning. ACM Trans. on Database Systems, 4, 4, 397-434. 48 http://www.kc.tsukuba.ac.jp/dlkc/e-proceedings/papers/dlkc04pp56.pdf
9. CRISP (2005) CRoss Industry Standard Process for Data Mining. http://www.crisp-dm.org/
10. Fayyad, U. M., Piatetsky-Shapiro, G., & Smyth, P. (1996). From data mining to knowledge discovery: An overview. In Advances in Knowledge Discovery and Data Mining. AAAI Press.
11. Huynh, T.N., Nguyen, B.T, Schiefer, J. and Tjoa, A.M. (2000) BEDAWA - A Tool for Generating Sample Data for Data Warehouses. Proc DaWaK 2000, London. pp 83-93. ISBN 3-540-67980-4 Springer Verlag, Berlin.
12. Han, J and Kamber, M. (2001) Data Mining: Concepts and Techniques. Morgan Kaufman.
13. Hand, D., Mannila, H., and Smyth, P. (2001) Principles of Data Mining. The MIT Press.
14. Tukey, J. W. (1977). Exploratory Data Analysis. Addison Wesley.
15. WEKA (2005) http://www.cs.waikato.ac.nz/ml/weka/
16. Witten, I, H. & Frank, E. (2000) Data Mining, Practical Machine Learning Techniques with Java Implementations. Academic Press.