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What is text mining, and how can it be used? What relevance do these methods have to everyday work in information science and the digital humanities? How does one develop competences in text mining? Working with Text provides a series of cross-disciplinary perspectives on text mining and its applications. As text mining raises legal and ethical issues, the legal background of text mining and the responsibilities of the engineer are discussed in this book. Chapters provide an introduction to the use of the popular GATE text mining package with data drawn from social media, the use of text mining to support semantic search, the development of an authority system to support content tagging, and recent techniques in automatic language evaluation. Focused studies describe text mining on historical texts, automated indexing using constrained vocabularies, and the use of natural language processing to explore the climate science literature. Interviews are included that offer a glimpse into the real-life experience of working within commercial and academic text mining. Introduces text analysis and text mining tools Provides a comprehensive overview of costs and benefits Introduces the topic, making it accessible to a general audience in a variety of fields, including examples from biology, chemistry, sociology, and criminology

Data mining. --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching

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Data Mining the Genomes, is the 23rd volume of the Stadler Symposia series published by Springer, which have served over many years as a comprehensive collection of current trends and emerging hot topics in the field of genetics. Data Mining the Genomes summarizes the progress in bioinformatics and computational biology in data mining the vast amount of exciting information emerging from studies of plant and animal genomes, with authoritative analytical reviews specialized enough to be attractive to professional researchers, yet also appealing to the wider audience of scientists in related disciplines. Data Mining the Genomes offers an essential reference material for any scientist or teacher working in the fields of bioinformatics, genomics, and genetics. All academics, scientists, and industry professionals wishing to take advantage of the latest and greatest in the continuously emerging field of bioinformatics will find it an invaluable resource. Key features: Comprehensive coverage of current topics Chapters authored by the key stars in the field Accessible utility in a single volume reference About the Editors: Perry Gustafson, PhD and Randy Shoemaker, PhD are Research Geneticists with the USDA-ARS, with Dr. Gustafson at the University of Missouri, Columbia and Dr. Shoemaker at Iowa State University, Ames. John Snape, PhD is a Research Geneticist at the John Innes Centre, Norwich, England. Collectively, Drs. Gustafson, Shomeaker, and Snape are associate editors on several international journals as well as having published numerous articles, review articles, and book chapters, in the field of genetics.

Genomics. --- Data mining. --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Genome research --- Genomes --- Molecular genetics --- Research

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Data mining --- Computer science --- Computer science. --- Data mining. --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Informatics --- Science

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data collection --- data management --- big data --- knowledge extraction --- Science --- Data mining --- Big data --- Big data. --- Data mining. --- Data processing --- Data processing. --- Electronic data processing --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Data sets, Large --- Large data sets --- Data sets --- Sciences - General --- Computer. Automation

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Data mining --- Exploration de donnés (Informatique) --- Information systems --- 681.3*E --- Management Information System --- econometrie --- wiskundige statistiek --- dataverwerking --- 681.3*E Data --- Data --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Data mining. --- Exploration de données (Informatique) --- Database searching --- Exploration de données (Informatique)