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1

Developments in data extraction, management, and analysis. Information Science Reference, 2012.

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2

Côte d'Ivoire. République de la Côte d'Ivoire, union-discipline-travail. Ministère d'Etat, Ministère du Plan et du Dèveloppement. Image économique des entreprises en 2005: Extraction de minérais métalliques. Institut national de la statistique, 2008.

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3

Petrucci, Alessandra, and Rosanna Verde, eds. SIS 2017. Statistics and Data Science: new challenges, new generations. Firenze University Press, 2017. http://dx.doi.org/10.36253/978-88-6453-521-0.

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The 2017 SIS Conference aims to highlight the crucial role of the Statistics in Data Science. In this new domain of ‘meaning’ extracted from the data, the increasing amount of produced and available data in databases, nowadays, has brought new challenges. That involves different fields of statistics, machine learning, information and computer science, optimization, pattern recognition. These afford together a considerable contribute in the analysis of ‘Big data’, open data, relational and complex data, structured and no-structured. The interest is to collect the contributes which provide from
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4

Liu, Huan. Feature Extraction, Construction and Selection: A Data Mining Perspective. Springer US, 1998.

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5

Bock, Hans-Hermann. Analysis of Symbolic Data: Exploratory Methods for Extracting Statistical Information from Complex Data. Springer Berlin Heidelberg, 2000.

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6

Côte d'Ivoire. République de la Côte d'Ivoire, union-discipline-travail. Ministère d'Etat, Ministère du Plan et du Dèveloppement. Image économique des entreprises en 2005: Extraction de pétrole brut et de gaz naturel. Institut national de la statistique, 2008.

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7

Frengen, Geir. Innovation in Norwegian manufacturing and oil extraction in 1992. Statistisk sentralbyrå, 1995.

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8

Whelan, Robert. Oregon's mineral industries: An assessment of the size and economic importance of mineral extraction in 1993. State of Oregon, Dept. of Geology and Mineral Industries, 1994.

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9

Wessel, Louis. Wyoming oil and natural gas extraction industry: A wage & employment survey, 1986. Wyoming Dept. of Labor & Statistics, 1986.

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10

Conference on Knowledge Extraction and Symbolic Data Analysis (1998 Luxembourg). Proceedings of the Conference on Knowledge Extraction and Symbolic Data Analysis: KESDA '98, Luxembourg, 27 to 28 April 1998. Office for Official Publications of the European Communities, 1999.

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11

Samuelsson, Christer. Statistical Methods. Edited by Ruslan Mitkov. Oxford University Press, 2012. http://dx.doi.org/10.1093/oxfordhb/9780199276349.013.0019.

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Statistical methods now belong to mainstream natural language processing. They have been successfully applied to virtually all tasks within language processing and neighbouring fields, including part-of-speech tagging, syntactic parsing, semantic interpretation, lexical acquisition, machine translation, information retrieval, and information extraction and language learning. This article reviews mathematical statistics and applies it to language modelling problems, leading up to the hidden Markov model and maximum entropy model. The real strength of maximum-entropy modelling lies in combining
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12

Chemometrics: Data Driven Extraction for Science. Wiley & Sons, Incorporated, John, 2018.

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13

Chemometrics: Data Driven Extraction for Science. Wiley, 2018.

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14

Brereton, Richard G. Chemometrics: Data Driven Extraction for Science. Wiley & Sons, Incorporated, John, 2018.

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15

Fogarty, Michael J., and Jeremy S. Collie. Fishery Ecosystem Dynamics. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780198768937.001.0001.

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This book provides an integrated framework for the quantitative analysis of exploited aquatic ecosystems, tracing the critical linkages between fundamental ecological processes and their implications for sustainable resource management. Examples are drawn from freshwater and marine ecosystems throughout the world. Fishery ecosystems have historically been subject to a broad array of human interventions, ranging from large-scale removal of biomass to deliberate attempts at ecosystem engineering involving species introductions, habitat alteration, and selective reorganization of ecosystem struct
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16

Extraction of Mineral Oil and Natural Gas: Business Monitor: Quarterly Statistics: Business Monitors: Quarterly Statistics. The Stationery Office Books, 1996.

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17

Britain, Great. Extraction of Mineral Oil and Natural Gas: Business Monitor: Quarterly Statistics: Business Monitors: Quarterly Statistics. The Stationery Office Books, 1996.

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18

van Dorp, Eveline L. A., Douglas Eleveld, Erik Olofsen, and Jaap Vuyk. Drug distribution and elimination in anaesthetic practice. Edited by Michel M. R. F. Struys. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780199642045.003.0012.

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An understanding of pharmacokinetics is vital for the practice of anaesthesia. Drugs are, after administration, distributed throughout the body to the effect site (mostly the brain) to exert their effects. This can be influenced by differences in protein binding, systemic blood flow, and concomitant medication. Elimination of drugs from the body is through two main routes: either unchanged through the kidneys or through metabolism by the liver (and consecutive excretion through the kidneys). This process depends on the amount of hepatic blood flow and the amount of hepatic extraction. This in
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19

Roe, Alan R., and Samantha Dodd. Dependence on extractive industries in lower-income countries: The statistical tendencies. UNU-WIDER, 2017. http://dx.doi.org/10.35188/unu-wider/2017/322-6.

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20

Roe, Alan, and Samantha Dodd. Dependence on Extractive Industries in Lower-income Countries. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198817369.003.0002.

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This chapter synthesizes statistical information evidencing the proposition that extractive industries are of great significance in many low- and middle-income developing economies, and so to their development prospects. It examines the scale of the current dependence of low- and middle-income economies on both types of extractive resources: metals, and oil and gas. The chapter also assesses how country levels of dependence have changed in the past twenty years, showing that there has been a clear upward trend based on exports. The chapter outlines how the upward trend has continued in many co
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21

Feature Extraction, Construction and Selection: A Data Mining Perspective. Springer, 2011.

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22

Wu, Hulin, Jose Miguel Yamal, Ashraf Yaseen, and Vahed Maroufy. Statistics and Machine Learning Methods for EHR Data: From Data Extraction to Data Analytics. Taylor & Francis Group, 2020.

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23

Statistics and Machine Learning Methods for EHR Data: From Data Extraction to Data Analytics. Taylor & Francis Group, 2020.

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24

Wu, Hulin, Jose Miguel Yamal, Ashraf Yaseen, and Vahed Maroufy. Statistics and Machine Learning Methods for EHR Data: From Data Extraction to Data Analytics. Taylor & Francis Group, 2020.

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25

Wu, Hulin, Jose Miguel Yamal, Ashraf Yaseen, and Vahed Maroufy. Statistics and Machine Learning Methods for EHR Data: From Data Extraction to Data Analytics. Taylor & Francis Group, 2020.

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26

Analysis of Symbolic Data: Exploratory Methods for Extracting Statistical Information from Complex Data. Springer, 2011.

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27

Boudreau, Joseph F., and Eric S. Swanson. Data modeling. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198708636.003.0016.

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A variety of techniques for extracting information from data are presented, from pedestrian approaches such as the centuries old linear least-squares fit, to elegant binned and unbinned likelihood fits. A treatment of statistical combination of data leads to an introduction to the powerful Kalman filter approach, used to determine optimal estimates of deterministic-stochastic systems. In experimental physics the Kalman filter is used estimate trajectories from data, but it also finds applications in industrial process control, and in the aeronautics and robots industries. These techniques typi
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28

Data Analysis Using the Method of Least Squares: Extracting the Most Information from Experiments. Springer, 2006.

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29

(Editor), Hans-Hermann Bock, and Edwin Diday (Editor), eds. Analysis of Symbolic Data: Exploratory Methods for Extracting Statistical Information from Complex Data (Studies in Classification, Data Analysis, and Knowledge Organization). Springer, 2000.

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30

Ericsson, Magnus, and Olof Löf. Mining’s Contribution to Low- and Middle-income Economies. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198817369.003.0003.

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In several low- and middle-income countries with important extractive sectors, gross national income has developed favourably. Africa has benefitted most, particularly West Africa. This chapter provides an up-to-date statistical analysis of the contribution of non-fuel minerals mining to low- and middle-income economies. Using the detailed data available for the minerals sector, an analysis is carried out of the current situation for 2014, and of trends in mining’s contribution to economic development for the years 1996–2014. The contribution of minerals and mining to gross domestic product an
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31

Hirschman, Lynette, and Inderjeet Mani. Evaluation. Edited by Ruslan Mitkov. Oxford University Press, 2012. http://dx.doi.org/10.1093/oxfordhb/9780199276349.013.0022.

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The commercial success of natural language (NL) technology has raised the technical criticality of evaluation. Choices of evaluation methods depend on software life cycles, typically charting four stages — research, advance prototype, operational prototype, and product. At the prototype stage, embedded evaluation can prove helpful. Analysis components can be loose grouped viz., segmentation, tagging, extracting information, and document threading. Output technologies such as text summarization can be evaluated in terms of intrinsic and extrinsic measures, the former checking for quality and in
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