Mining Complex Hydrobiological Data with Galois Lattices

We have used Galois lattices for mining hydrobiological data. These data are about macrophytes, that are macroscopic plants living in water bodies. These plants are characterized by several biological traits, that own several modalities. Our aim is to cluster the plants according to their common traits and modalities and to find out the relations between traits. Galois lattices are efficient methods for such an aim, but apply on binary data. In this article, we detail a few approaches we used to transform complex hydrobiological data into binary data and compare the first results obtained thanks to Galois lattices

GCG: Mining Maximal Complete Graph Patterns from Large Spatial Data

Recent research on pattern discovery has progressed from mining frequent patterns and sequences to mining structured patterns, such as trees and graphs. Graphs as general data structure can model complex relations among data with wide applications in web exploration and social networks. However, the process of mining large graph patterns is a challenge due to the existence of large number of subgraphs. In this paper, we aim to mine only frequent complete graph patterns. A graph g in a database is complete if every pair of distinct vertices is connected by a unique edge. Grid Complete Graph (GCG) is a mining algorithm developed to explore interesting pruning techniques to extract maximal complete graphs from large spatial dataset existing in Sloan Digital Sky Survey (SDSS) data. Using a divide and conquer strategy, GCG shows high efficiency especially in the presence of large number of patterns. In this paper, we describe GCG that can mine not only simple co-location spatial patterns but also complex ones. To the best of our knowledge, this is the first algorithm used to exploit the extraction of maximal complete graphs in the process of mining complex co-location patterns in large spatial dataset.Comment: 1

Complex Data: Mining using Patterns

There is a growing need to analyse sets of complex data, i.e., data in which the individual data items are (semi-) structured collections of data themselves, such as sets of time-series. To perform such analysis, one has to redefine familiar notions such as similarity on such complex data types. One can do that either on the data items directly, or indi- rectly, based on features or patterns computed from the individual data items. In this paper, we argue that wavelet decomposition is a general tool for the latter approac

DAMEWARE - Data Mining & Exploration Web Application Resource

Astronomy is undergoing through a methodological revolution triggered by an unprecedented wealth of complex and accurate data. DAMEWARE (DAta Mining & Exploration Web Application and REsource) is a general purpose, Web-based, Virtual Observatory compliant, distributed data mining framework specialized in massive data sets exploration with machine learning methods. We present the DAMEWARE (DAta Mining & Exploration Web Application REsource) which allows the scientific community to perform data mining and exploratory experiments on massive data sets, by using a simple web browser. DAMEWARE offers several tools which can be seen as working environments where to choose data analysis functionalities such as clustering, classification, regression, feature extraction etc., together with models and algorithms.Comment: User Manual of the DAMEWARE Web Application, 51 page

Simulation of deposit parameters in underground development mining

The article is aimed at improving development mining to prepare an ore body for stoping by access ramps to provide comfortable conditions and high technical and economic indices in underground mining. Efficient parameters of underground mining are chosen in the course of simulating data on the mining theory and practice considering ore losses and dilution on the basis of critical analysis of uranium mining enterprises’ activities. The research provides data on geological and engineering zoning of an ore deposit and physical-mechanical properties of ore bearing rocks. The advanced experience is systemized and there is provided system analysis of modern development mining schemes with access ramps (ring, spiral, one-way inclined, central inclined and across the strike). The research recommends schemes of development mining and substantiates their advantages. There are quantitative indices of physical simulation of development variants as to drawn ore quality according to criteria of soil location in ore draw points. The scientific novelty implies developing the criterion of optimality and ranking variants of development mining according to technical-economic and geomechanical indices considering some technological factors as well as the number of stopes operating simultaneously on the level. The study consists in increasing authenticity of development projects through applying complex schemes of access ramps according to the complex criterion of increasing mining depths, equipment application, ventilation and underground mine capacity