This study discusses how to maintain discovered sequential patterns when some information is deleted from a sequence database. A new algorithm, called MA_D (Maintenance Algorithm when Deleting some information), is presented in order to deal with the maintenance of sequential patterns mining resulted from the updating of database and the algorithm makes full use of the information obtained from...

In this chapter I begin by discussing Distributed Data Mining (DDM) for scaling up, beginning by asking what scaling up means, questioning whether it is necessary, and then presenting a brief survey of what has been done to date. I then provide motivation beyond scaling up, arguing that DDM is a more natural way to view data mining generally. DDM eliminates many difficulties encountered when co...

The mining industry relies heavily on empirical analysis for design and prediction. An empirical design method, called the critical span graph, was developed specifically for rock stability analysis in entry-type excavations, based on an extensive case-history database of cut and fill mining in Canada. This empirical span design chart plots the critical span against rock mass rating for the obs...

Information has become a commodity, moving from place to place with little thought given to the ultimate value provided to consumers, business, and society. With advanced innovations in e-business, data warehousing, and data mining, it is becoming increasingly important to look at the impact of information use on individuals. This free flow of information within an organization and between diff...

This work describes the development of Enterprise Architect Unified Modeling Language (ea UML) – Microsoft SQL Server – Borland C ++ Builder information model for qualitative operation of open-cast mining and transport systems including description of process, technical and organizational factors influencing on the efficiency of mining and transport operations processes. For simulation (imitati...

Many data mining problems can be solved better if they are augmented with additional background knowledge. This paper discusses a framework of adding background knowledge from Linked Open Data to a given data mining problem in a fully automatic, unsupervised manner. It introduces the FeGeLOD framework and its latest implementation, the RapidMiner Linked Open Data extension. We show the use of t...

This chapter discusses four-selected software for data mining that are not available as free open-source software. The four-selected software for data mining are SAS® Enterprise MinerTM, Megaputer PolyAnalyst® 5.0, NeuralWare Predict® and BioDiscovery GeneSight®, each of which was provided by partnerships with our university. These software are described and compared by their existing features,...

One of the most difficult challenges facing coal mining industry is rehabilitation open cut mines in absence sufficient quality and quantity topsoil. As a result, growth medium for often mine spoil that has poor chemical structural properties. Microorganisms play critical role natural soil forming processes, nutrient cycling aggregate stabilisation. However, microbiota their impact on chemistry...

Traditional optimization of open pit mine design is a crucial component mining endeavors and influenced by many variables. The critical factor in the geological uncertainty, which relates to ore grade. To deal with uncertainties related block economic values blocks general problem optimization, under unknown conditions, best ultimate limits pushback designs are produced minimum cut algorithm. p...