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- Towards Data Quality and Data Mining Using Constraints in XML
- Quality data is necessary for different data mining techniques and reversely, data mining techniques can be utilized to measure quality of data. Data mining and data quality issues got much attention for relational data in past. But, as a massive amount of data is being stored and represented over the...
- White papers 2009-03-01
- Short Paper: Data Mining-Based Fault Prediction and Detection on the Grid
- This paper describes a novel approach to fault detection and prediction on the Grid based on data mining techniques. Data mining techniques are here applied as a mean to effectively process the significant amount of captured data from Grid sites, services, workflows and activities. The paper provides a first approach...
- White papers 2006-06-12
Additional Resources
- Data Mining for Intelligence Led Policing
- The benefit of data mining for police seems tremendous, yet only a few limited applications are documented. This paper starts with describing the implementation problems of police data mining and introduces a new approach that tries to overcome these problems in the form of a data mining system with associative...
- White papers 2009-06-05
- 2D CAD Data Mining Based on Spatial Relation
- This paper proposes CAD data mining technique to obtain semantic elements without prior knowledge about plans being designed. The method consists of two steps. The first step is to extract frequent spatial relations between figure elements in CAD data as clues to the semantic elements. These relations are modeled as...
- White papers 2009-05-30
- Data Mining Storm Attributes From Spatial Grids
- A technique to identify storms and capture scalar features within the geographic and temporal extent of the identified storms is described. The identification technique relies on clustering grid points in an observation field to find self-similar and spatially coherent clusters that meet the traditional understanding of what storms are. From...
- White papers 2009-04-30
- A Hybrid Data Mining Metaheuristic for the p-Median Problem
- Metaheuristics represent an important class of techniques to solve, approximately, hard combinatorial optimization problems for which the use of exact methods is impractical. In this work, one proposes a hybrid version of the GRASP metaheuristic, which incorporates a data mining process, to solve the p-median problem. The paper believes that...
- White papers 2009-02-23
- Methodology of Adaptation of Data Mining Methods for Medical Decision Support: Case Study
- Data mining is a problem solving technique, which analyzes the data already stored in the data base. It is a process of discovering, classifying and finding patterns in data. The classification of data helps to make a decision in different types of problems. Machine Learning, Statistical and Neural Network algorithms...
- White papers 2009-02-09
- Performance Intelligence: BI for Database Performance
- Ignite Performance Intelligence™ is a database performance analysis technique that identifies the most important database performance problems and their resolution. Performance Intelligence takes proven business intelligence techniques and applies them to IT performance management. By capturing and analyzing data in a data warehouse, it identifies trends, reveals anomalies and correlates...
- White papers 2008-12-02
- A Real-Time Intrusion Detection System Using Data Mining Technique
- Presently, most computers authenticate user ID and password before users can login these systems. However, danger soon comes if the two items are known to hackers. This paper, proposes a system, named Intrusion Detection and Identification System IDIS, which builds a profile for each user in an intranet to keep...
- White papers 2008-08-28
- Medical Image Classification Using an Efficient Data Mining Technique
- Data mining refers to extracting or "Mining" knowledge from large amounts of data. It is an increasingly popular field that uses statistical, visualization, machine learning, and other data manipulation and knowledge extraction techniques aimed at gaining an insight into the relationships and patterns hidden in the data. Availability of digital...
- White papers 2008-05-15
- Spatial Data Mining for Retail Sales Forecasting
- This paper presents a use case of spatial data mining for aggregate sales forecasting in retail location planning. In particular, the data mining technique Support Vector Regression SVR is used to design a regression model to predict probable turnovers for potential outlet-sites of a big European food retailing company. The...
- White papers 2008-04-02
- Cross-SAGE: SAGE Data Mining Tool Based on Set Theory
- SAGE Serial Analysis of Gene Expression is a technique for analyzing gene expression of a series of tags obtained from cDNA. This technology lets biologists analyze and observe the relative gene expressions of many samples in silico. To date, some visible analyzing platforms for SAGE were not provided in a...
- White papers 2008-03-21
- Two-Stage Variable Clustering for Large Data Sets
- In data mining, principal component analysis is a popular dimension reduction technique. It also provides a good remedy for the multicollinearity problem, but its interpretation of input space is not as good. To overcome the interpretation problem, principal components cluster components are obtained through variable clustering, which was implemented with...
- White papers 2008-02-15
- MINDS - Minnesota Intrusion Detection System
- This paper introduces the Minnesota Intrusion Detection System MINDS, which uses a suite of data mining techniques to automatically detect attacks against computer networks and systems. While the long-term objective of MINDS is to address all aspects of intrusion detection, this paper focuses on two specific contributions: an unsupervised anomaly...
- White papers 2008-01-01
- A Data Mining Technique to Detect Remote Exploits
- This paper designed and implemented DExtor, a Data Mining based Exploit code detector, to protect network services. The main assumption of the work is that normal traffic into the network services contain only data, whereas exploit code contains code. Thus, the "Exploit code detection" problem reduces to "Code detection" problem....
- White papers 2007-12-20
- Looking inside our skin
- Researchers from the European Molecular Biology Laboratory EMBL have taken the closest look ever at native human tissue by using an advanced microscopy technique called cryo-electron tomography. This technique allows to obtain molecular resolution images of intact cells. The researchers were able to reveal the Velcro-like molecular organization of...
- Blog posts 2007-12-10
- Assessing Data Mining Results Via Swap Randomization
- The problem of assessing the significance of data mining results on high-dimensional 0 - 1 datasets has been studied extensively in the literature. For problems such as mining frequent sets and finding correlations, significance testing can be done by standard statistical tests such as chi-square, or other methods. However, the...
- White papers 2007-12-01
- Neuro Genetic-Nearest Neighbor Based Data Mining Techniques for Fingerprint Classification and Recognition System
- The proposed fingerprint classification using Data Mining technique, Neuro Genetic-Nearest Neighbor based recognition, overcomes low recognition rate, low accuracy, increased time of recovery and improves the classification rate. The proposed method involves various stages like image enhancement, line detector based feature extraction and neural network classification using Learning Vector Quantization...
- White papers 2007-11-01
- Adapting the Fitness Function in GP for Data Mining
- This paper describes how the Stepwise Adaptation of Weights saw technique can be applied in genetic programming. The sawing mechanism has been originally developed for and successfully used in EAs for constraint satisfaction problems. Here the paper identifies the very basic underlying ideas behind sawing and point out how it...
- White papers 2007-10-09
- A SOM-Based Data Mining Strategy for Adaptive Modelling of an Offset Lithographic Printing Process
- This paper is concerned with a SOM-based data mining strategy for adaptive modelling of a slowly-varying process. The aim is to follow the process in a way that makes a representative up-to-date data set of a reasonable size available at any time. The technique developed allows analysis and filtering of...
- White papers 2007-10-03
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