Xiaolei Yuan. / Thesis submitted in: December 2003. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2004. / Includes bibliographical references (leaves 95-101). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Background --- p.1 / Chapter 1.1.1 --- Data Mining: A New Wave of Database Applications --- p.1 / Chapter 1.1.2 --- Association Rule Mining --- p.4 / Chapter 1.2 --- Motivation --- p.7 / Chapter 1.3 --- Main Contribution --- p.8 / Chapter 1.4 --- Thesis Organization --- p.9 / Chapter 2 --- Literature Review --- p.10 / Chapter 2.1 --- Data mining and association rule mining --- p.10 / Chapter 2.2 --- Integration data mining with DBMS --- p.11 / Chapter 2.3 --- Query language design for association rule mining --- p.12 / Chapter 2.4 --- Unified data mining models --- p.15 / Chapter 2.5 --- Other topics --- p.15 / Chapter 3 --- A New Data Mining Query Language M2MQL --- p.17 / Chapter 3.1 --- Simple item-based association rule --- p.18 / Chapter 3.1.1 --- One rule set --- p.19 / Chapter 3.1.2 --- Rule set and Source data set --- p.22 / Chapter 3.1.3 --- New rule sets from existing ones --- p.24 / Chapter 3.2 --- Generalized item-based association rules --- p.25 / Chapter 3.3 --- CREATE RULE and SELECT RULE Primitive --- p.32 / Chapter 4 --- The Algebra in M2MQL --- p.33 / Chapter 4.1 --- Review of nested relations --- p.33 / Chapter 4.1.1 --- Concepts of nested relation --- p.34 / Chapter 4.1.2 --- Nested relation and association rule mining --- p.35 / Chapter 4.2 --- Nested relational algebra --- p.36 / Chapter 4.3 --- Specific data mining algebra --- p.39 / Chapter 4.3.1 --- POWERSET p --- p.40 / Chapter 4.3.2 --- SET-CONTAINMENT-JOIN xc --- p.40 / Chapter 4.3.3 --- Functional operators --- p.42 / Chapter 5 --- Mining On Top of M2MQL --- p.50 / Chapter 5.1 --- Problem statement --- p.50 / Chapter 5.2 --- Frequency Counting Phase --- p.52 / Chapter 5.3 --- Frequent Itemset Generation Phase --- p.54 / Chapter 5.4 --- Rule Generation Phase --- p.57 / Chapter 5.5 --- Summary --- p.64 / Chapter 6 --- Conclusions and Future Work --- p.65 / Chapter 6.1 --- What we have achieved --- p.65 / Chapter 6.2 --- What is ahead --- p.66 / Chapter 6.2.1 --- Issues of Query Optimization --- p.66 / Chapter 6.2.2 --- Issues of Expanding Table Forms --- p.67 / Chapter A --- General Syntax of M2MQL --- p.68 / Chapter B --- Syntax and Example for MSQL --- p.71 / Chapter B.1 --- Syntax of MSQL --- p.71 / Chapter B.2 --- Example --- p.73 / Chapter C --- Syntax and Example for MINE RULE --- p.76 / Chapter C.1 --- syntax of MINE RULE --- p.76 / Chapter C.2 --- Example --- p.77 / Chapter C.2.1 --- Counting Groups --- p.78 / Chapter C.2.2 --- Making Couples of Clusters --- p.79 / Chapter C.2.3 --- Extracting Bodies --- p.80 / Chapter C.2.4 --- Extracting Rules --- p.80 / Bibliography --- p.83

Cheung, Yin-ling. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2001. / Includes bibliographical references (leaves 117-124). / Abstracts in English and Chinese. / Abstract --- p.ii / Acknowledgement --- p.iv / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Data Mining Techniques --- p.1 / Chapter 1.1.1 --- Classification --- p.1 / Chapter 1.1.2 --- Association Rules Mining --- p.2 / Chapter 1.1.3 --- Estimation --- p.2 / Chapter 1.1.4 --- Prediction --- p.2 / Chapter 1.1.5 --- Clustering --- p.2 / Chapter 1.1.6 --- Description --- p.3 / Chapter 1.2 --- Problem Definition --- p.3 / Chapter 1.3 --- Thesis Organization --- p.4 / Chapter I --- Decision Tree Classifiers --- p.6 / Chapter 2 --- Background --- p.7 / Chapter 2.1 --- Introduction to Classification --- p.7 / Chapter 2.2 --- Classification Using Decision Trees --- p.8 / Chapter 2.2.1 --- Constructing a Decision Tree --- p.10 / Chapter 2.2.2 --- Related Work --- p.11 / Chapter 3 --- Strategies to Enhance the Performance in Building Decision Trees --- p.14 / Chapter 3.1 --- Introduction --- p.15 / Chapter 3.1.1 --- Related Work --- p.15 / Chapter 3.1.2 --- Post-evaluation vs Pre-evaluation of Splitting Points --- p.19 / Chapter 3.2 --- Schemes to Construct Decision Trees --- p.27 / Chapter 3.2.1 --- One-to-many Hashing --- p.27 / Chapter 3.2.2 --- Many-to-one and Horizontal Hashing --- p.28 / Chapter 3.2.3 --- A Scheme using Paired Attribute Lists --- p.29 / Chapter 3.2.4 --- A Scheme using Database Replication --- p.31 / Chapter 3.3 --- Performance Analysis --- p.32 / Chapter 3.4 --- Experimental Results --- p.38 / Chapter 3.4.1 --- Performance --- p.38 / Chapter 3.4.2 --- Test 1 : Smaller Decision Tree --- p.40 / Chapter 3.4.3 --- Test 2: Bigger Decision Tree --- p.44 / Chapter 3.5 --- Conclusion --- p.47 / Chapter II --- Mining Association Rules --- p.48 / Chapter 4 --- Background --- p.49 / Chapter 4.1 --- Definition --- p.49 / Chapter 4.2 --- Association Algorithms --- p.51 / Chapter 4.2.1 --- Apriori-gen --- p.51 / Chapter 4.2.2 --- Partition --- p.53 / Chapter 4.2.3 --- DIC --- p.54 / Chapter 4.2.4 --- FP-tree --- p.54 / Chapter 4.2.5 --- Vertical Data Mining --- p.58 / Chapter 4.3 --- Taxonomies of Association Rules --- p.58 / Chapter 4.3.1 --- Multi-level Association Rules --- p.58 / Chapter 4.3.2 --- Multi-dimensional Association Rules --- p.59 / Chapter 4.3.3 --- Quantitative Association Rules --- p.59 / Chapter 4.3.4 --- Random Sampling --- p.60 / Chapter 4.3.5 --- Constraint-based Association Rules --- p.60 / Chapter 5 --- Mining Association Rules without Support Thresholds --- p.62 / Chapter 5.1 --- Introduction --- p.63 / Chapter 5.1.1 --- Itemset-Loop --- p.66 / Chapter 5.2 --- New Approaches --- p.67 / Chapter 5.2.1 --- "A Build-Once and Mine-Once Approach, BOMO" --- p.68 / Chapter 5.2.2 --- "A Loop-back Approach, LOOPBACK" --- p.74 / Chapter 5.2.3 --- "A Build-Once and Loop-Back Approach, BOLB" --- p.77 / Chapter 5.2.4 --- Discussion --- p.77 / Chapter 5.3 --- Generalization: Varying Thresholds Nk for k-itemsets --- p.78 / Chapter 5.4 --- Performance Evaluation --- p.78 / Chapter 5.4.1 --- Generalization: Varying Nk for k-itemsets --- p.84 / Chapter 5.4.2 --- Non-optimal Thresholds --- p.84 / Chapter 5.4.3 --- "Different Decrease Factors,f" --- p.85 / Chapter 5.5 --- Conclusion --- p.87 / Chapter 6 --- Mining Interesting Itemsets with Item Constraints --- p.88 / Chapter 6.1 --- Introduction --- p.88 / Chapter 6.2 --- Proposed Algorithms --- p.91 / Chapter 6.2.1 --- Single FP-tree Approach --- p.92 / Chapter 6.2.2 --- Double FP-trees Approaches --- p.93 / Chapter 6.3 --- Maximum Support Thresholds --- p.102 / Chapter 6.4 --- Performance Evaluation --- p.103 / Chapter 6.5 --- Conclusion --- p.109 / Chapter 7 --- Conclusion --- p.110 / Chapter A --- Probabilistic Analysis of Hashing Schemes --- p.112 / Chapter B --- Hash Functions --- p.114 / Bibliography --- p.117

No description available.

A presente tese apresenta uma contribuição técnico-econômica à atual mineração brasileira de fluorita, que foi profundamente modificada pelo desenvolvimento de novos e importantes depósitos. Tendo-se em vista a importância econômica do mineral, no atual contexto industrial, são analisados os usos e aplicações da fluorita, as principais propriedades físico-químicas do elemento flúor e de seus minerais, bem como as características estruturais e genéticas dos depósitos minerais que condicionam o aproveitamento industrial. Essa abordagem tem por objetivo não somente rememorar os conhecimentos técnicos, como também investigar as conexões que devem existir entre as várias fases de desenvolvimento pelas quais um empreendimento mineiro passa até a sua consolidação. Diversos fatores técnicos pertinentes à indústria mineral são discutidos, com ênfase às características peculiares da mineração de fluorita, incluindo a recente usina de beneficiamento inaugurada no Alto Vale do Ribeira, no Estado do Paraná. Os aspectos relativos à produção, custos e mercados são examinados no âmbito do comércio nacional e internacional. Finalmente, a demanda futura da fluorita na indústria nacional é estimada com base no crescimento acelerado da produção brasileira de aço bruto e alumínio primário. / This thesis is a contribution to the present technical and economical aspects of the brazilian fluorite mining industry, which hás been deeply affected by recent development of several importants deposits. Due to the economic importance of fluorite for the brazilian industry, its main applications are analysed, along with consideration on the physico - chemical properties of fluorine and associated important mineral. Genetic and structural characteristics of the mineral deposits affecting the industrial recovery of fluorite are also discussed. Throughout the whole report there is a search for the linking elements that must exist between the several phases of a complete mining Project, from the initial stages up to the operation point. A brief review of the existing operating and their technical characteristics is presented, i8ncluding some details of a fluorite Project recently started at the Upper Vale do Ribeira, in the Paraná State. Production, cost and market aspects are examined from national and international viewpoints, and finally future consumption trends are evaluated, considering the rapi evolution of the raw steel and primary aluminum productions.

Thesis (Ph. D.)--University of Hong Kong, 2007. / Title proper from title frame. Also available in printed format.

This thesis presents a novel application of structural reliability concepts to assess the reliability of mining operations. “Limit-states” are defined to obtain the probability that the total productivity — measured in production time or economic gain — exceeds user-selected thresholds. Focus is on the impact of equipment downtime and other non-operating instances on the productivity and the economic costs of the operation. A comprehensive set of data gathered at a real-world mining facility is utilized to calibrate the probabilistic models. In particular, the utilization of Bayesian inference facilitates the inclusion of data — and updating of the production probabilities — as they become available. The thesis includes a detailed description of the Bayesian approach, as well as the limit-state-based reliability methodology. A comprehensive numerical example demonstrates the methodology and the usefulness of the probabilistic results.

Univ., Diss.--Frankfurt am Main, 2007.

Univ., Diss--Würzburg, 2006.

Thesis (M.S.)--Kutztown University of Pennsylvania, 2009. / Source: Masters Abstracts International, Volume: 47-05, page: 2936. Adviser: Randy Kaplan. Bibliographical references (p. 50-52)

Thesis--Auburn University, 2009. / Abstract. Includes bibliographic references (p.31-33).