By Alfio Vidotto, Kenneth N. Brown, J. Christopher Beck (auth.), Richard Ellis BSc, MSc, Dr Tony Allen PhD, Dr Andrew Tuson MA, MSc, PhD, MBCS (eds.)
APPLICATIONS AND suggestions IN clever structures XIV
The papers during this quantity are the refereed software papers provided at AI-2006, the Twenty-sixth SGAI overseas convention on cutting edge options and functions of man-made Intelligence, held in Cambridge in December 2006.
The papers during this quantity current new and leading edge advancements within the box, divided into sections on info Mining and Bayesian Networks; Genetic Algorithms and Optimisation strategies; brokers and Semantic net; and traditional Language.
This is the fourteenth quantity within the purposes and thoughts sequence. The sequence serves as a key reference as to how AI expertise has enabled corporations to resolve complicated difficulties and achieve major enterprise benefit.
The Technical flow papers are released as a better half quantity less than the name learn and improvement in clever platforms XXIII.
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Additional resources for Applications and Innovations in Intelligent Systems XIV: Proceedings of AI-2006, the Twenty-sixth SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence
Com). Initially, it is important to have a clear understanding of the business domain in order to understand the operational analytical processes , the problems that are to be surmounted, the opportunities that may be realised and to assess the availability of data. Exploring and preparing the data, although time consuming, is a crucial stage in the cycle. New fields may be derived from one or more existing fields, missing and boundary values identified and processed, relationships between fields and records identified form some ofthe pre-processing tasks that assist in cleaning the data prior to the mining process.
Quinlan J, R,. (1996). 5 Proceedings J Conference on Artificial Intelligence, August 4 - 8. Portland USA. r National 25. >. (accessed on 5th June 2000) 26. Sherman, R. (2005). Data integration advisor: set the stage with data preparation, DMReview, February 1005. 27. Swingler, K. (1996). Applying Neuralblnetworks; A Practical Guide. San Francisco: Morgan Kaufman 28. Thomsen, E. (1998). Presentation: Very Large Data Bases / Data Mining Summit, Beverly Hills, California. 29. Tilley N, Ford A. (1996).
High collection rates for DNA but not for fingerprints 3. High collection rates for fingerprints, but low for DNA 4. Low collection rates for both DNA and fingerprints This lead us to speculate that as many as four clusters (or 'types') of CSls might exist within the data set. The K-Means algorithm was run on two different data sets, CSI activities where fingerprints and DNA were recovered and activities where the recovery lead to an individual person being identified. Table I below illustrates the results of the clustering process.