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1

McLean, Gerald. More like this: Development of digital file management methodologies (including linking to text data) for integrating text and images. London: LCP, 2003.

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2

Keyes, Bettye. Voice writing method. Little Rock, Ark: VoiceCAT Corp., 2005.

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3

1948-, Fogelman-Soulié Françoise, North Atlantic Treaty Organization. Public Diplomacy Division, and ebrary Inc, eds. Mining massive data sets for security: Advances in data mining, search, social networks and text mining, and their applications to security. Amsterdam: IOS Press, 2008.

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4

Thanassoulis, Emmanuel. Introduction to the theory and application of data envelopment analysis: A foundation text with integrated software. Norwell, Mass: Kluwer Academic Publishers, 2001.

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5

Analyzing streams of language: Twelve steps to the systematic coding of text, talk, and other verbal data. New York: Longman, 2003.

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6

Bateson, Teresa M. Report on parsing and construction of prototype that will accept freeform text data from publishers' sites and parse this data for automatic entry to book database. [s.l: The Author], 2001.

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7

Schneider, G. Michael. Modula-2 supplement to accompany 'Concepts in data structures and software development': A text for the second course inComputer Science. St. Paul, MN: West Publishing Co., 1991.

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8

Schneider, G. Michael. ADA supplement to accompany 'Concepts in data structures and software development': A text for the second course in Computer Science. St. Paul, MN: West Publishing Co., 1991.

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9

Kōpasu to tekisuto mainingu: Corpus & text mining. Tōkyō-to Bunkyō-ku: Kyōritsu Shuppan, 2012.

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10

Marchese, Francis T. Knowledge Visualization Currents: From Text to Art to Culture. London: Springer London, 2013.

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11

Schneider, G. Michael. C and C (plus plus) supplement to accompany 'Concepts in data structures and software development': A text for the second course in Computer Science. St. Paul, MN: West Publishing Co., 1991.

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12

Weiner, John M. Knowledge utilization: Paths to creativity. Gallatin, TN: XXIV Century Press, 2005.

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13

Text generation: Using discourse strategies and focus constraints to generate natural language text. Cambridge [Cambridgeshire]: Cambridge University Press, 1985.

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14

Joachims, Thorsten. Learning to Classify Text Using Support Vector Machines. Boston, MA: Springer US, 2002.

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15

Thomas S. Morton Grant S. Ingersoll. Taming Text: How to Find, Organize, and Manipulate It. [S.l.]: Manning Publications, 2012.

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16

service), SpringerLink (Online, ed. Journeys to Data Mining: Experiences from 15 Renowned Researchers. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.

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17

Scalzo, Bert. Oracle on VMware: From laptops to production. Kittrell, N.C: Rampant Techpress, 2008.

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18

Oracle on VMware: From laptops to production. Kittrell, N.C: Rampant Techpress, 2008.

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19

Gonnet, G. H. Mind your grammar: A new approach to modelling text. Waterloo, Ont: UW Centre for the New Oxford English Dictionary, 1987.

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20

Time-constrained memory: A reader-based approach to text comprehension. Hillsdale, N.J: L. Erlbaum Associates, 1995.

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21

DeRose, Steven J. Making Hypermedia Work: A User's Guide to HyTime. Boston, MA: Springer US, 1994.

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22

Lau, Ken. Learning to become a professional in a textually-mediated world: A text-oriented study of placement practices. Bern: Peter Lang, 2012.

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23

Ensor, Pat. CD-ROM research collections: An evaluative guide to bibliographic and full-text CD-ROM databases. Westport: Meckler, 1991.

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24

All roads lead to the Text: Eight methods of inquiry into the bible : a template for model exegesis with exegetical examples employing Logos Bible Software. Grand Rapids, Mich: W.B. Eerdmans Pub. Co., 2011.

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25

Beaugrande, Robert De. New foundations for a science of text and discourse: Cognition, communication, and the freedom of access to knowledge and society. Norwood, N.J: Ablex, 1997.

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26

Tenopir, Carol. Managing yourinformation: How to design and create a textual data base on your Microcomputer. New York: Neal-Schuman, 1988.

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27

Read between the lines: A humorous guide to texting with simplicity and style. Dallas, Tex: Brown Books, 2010.

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28

GOVERNMENT, US. An Act to Make Available Certain Voice of America and Radio Marti Multilingual Computer Readable Text and Voice Recordings. [Washington, D.C.?: U.S. G.P.O., 1996.

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29

Brommer, Sarah. Sprachliche Muster. Berlin, Boston: De Gruyter, 2018. http://dx.doi.org/10.1515/9783110573664.

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Abstract The study examines patterns of language usage in scientific texts and describes the academic style based on a data-derived corpus analysis at the formal and pragmatic levels. Theoretically grounded in multiple linguistic subdisciplines, the book offers an important contribution to the description of text types, the discussion of norms, and research on writing.
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30

Tools for Humanists (1989 Toronto, Ont.). Tools for Humanists, 1989: A guidebook to the software and hardware fair held in conjunction with The dynamic text : the 9th International Conference on Computers and the Humanities (ICCH) and the 16th International Association for Literary and Linguistic Computing (ALLC) Conference. Toronto, Ont., Canada: Centre for Computing in the Humanities, University of Toronto, 1989.

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31

Deep Text: Using Text Analytics to Conquer Information Overload, Get Real Value from Social Media, and Add Bigger Text to Big Data. Information Today Inc, 2016.

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32

author, Mihalcea Rada 1974, ed. An introduction to text mining: Research design, data collection, and analysis. SAGE Publications, Inc, 2018.

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33

Dalrymple, Douglas J. Dalrymple: IBM Data/Lotus Disk to Accompany Marketing Management: Text & Cases 5ed (Disk). John Wiley & Sons Inc, 1992.

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34

Automated Data Collection with R: A Practical Guide to Web Scraping and Text Mining. Wiley, 2015.

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35

Introduction to Concepts and Techniques in Data Mining and Application to Text Mining(Techniques to transform data and information into knowledge with plenty of comprehensible examples). Thammasat Printing House, 2012.

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36

Newby, Cynthia. From Patient to Payment: Insurance Procedures for the Medical Office, Student Text with Data Disk. McGraw-Hill Science/Engineering/Math, 2001.

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37

Newby, Cynthia. From Patient to Payment: Insurance Procedures for the Medical Office, Student Text with Data Disk. 3rd ed. McGraw-Hill Science/Engineering/Math, 2001.

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38

Mark, James E. Polymer Data Handbook: On-line access to full text available with purchase; instructions in book. Oxford University Press, USA, 1999.

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39

Higgins, James M. Case financial data to accompany Instructor's manual for Strategic management : Text and cases, fifth edition. Dryden Press, 1993.

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40

Thanassoulis, Emmanuel. Introduction to the Theory and Application of Data Envelopment Analysis: A Foundation Text with Integrated Software. Springer, 2013.

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41

Text Analytics with Python: A Practical Real-World Approach to Gaining Actionable Insights from your Data. Apress, 2016.

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42

Thanassoulis, Emmanuel. Introduction to the Theory and Application of Data Envelopment Analysis - A Foundation Text with Integrated Software. Springer, 2001.

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43

Brian, Fessler, Cassidy W. A, and United States. National Aeronautics and Space Administration., eds. Antarctic meteorite location and mapping project (AMLAMP): Antarctic meteorite location map series explanatory text and user's guide to AMPLAMP data. Houston, Texas: Lunar and Planetary Institute, 1993.

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44

Antarctic meteorite location and mapping project (AMLAMP): Antarctic meteorite location map series explanatory text and user's guide to AMPLAMP data. Houston, Texas: Lunar and Planetary Institute, 1993.

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45

Christiansen, Stacy. Visual Presentation of Data. Oxford University Press, 2009. http://dx.doi.org/10.1093/jama/9780195176339.003.0004.

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Tables and figures demonstrate relationships among data and other types of information. A well-structured table is perhaps the most efficient way to convey a large amount of data in a scientific manuscript. As text, the same information may take considerably more space; if presented in a figure, key details and precise values may be less apparent. Text may be preferred if the information can be presented concisely (see Box). For qualitative information, text should be used if the relationships among data are simple and data are few, whereas a figure should be used if the relationships are complex. For quantitative information, a table should be used when the display of exact values is important, whereas a figure (eg, a line graph) should be used to demonstrate patterns or trends. Tables also are often preferable to graphics for small data sets and are preferred when data presentation requires many specific comparisons...
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46

Marchese, Francis T., and Ebad Banissi. Knowledge Visualization Currents: From Text to Art to Culture. Springer, 2014.

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47

Mehler, Alexander, and Chris Biemann. Text Mining: From Ontology Learning to Automated Text Processing Applications. Springer, 2016.

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48

Mehler, Alexander, and Chris Biemann. Text Mining: From Ontology Learning to Automated Text Processing Applications. Springer, 2014.

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49

Raychaudhuri, Soumya. Computational Text Analysis. Oxford University Press, 2006. http://dx.doi.org/10.1093/oso/9780198567400.001.0001.

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This book brings together the two disparate worlds of computational text analysis and biology and presents some of the latest methods and applications to proteomics, sequence analysis and gene expression data. Modern genomics generates large and comprehensive data sets but their interpretation requires an understanding of a vast number of genes, their complex functions, and interactions. Keeping up with the literature on a single gene is a challenge itself-for thousands of genes it is simply impossible. Here, Soumya Raychaudhuri presents the techniques and algorithms needed to access and utilize the vast scientific text, i.e. methods that automatically "read" the literature on all the genes. Including background chapters on the necessary biology, statistics and genomics, in addition to practical examples of interpreting many different types of modern experiments, this book is ideal for students and researchers in computational biology, bioinformatics, genomics, statistics and computer science.
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50

Text me: Everything you need to know about text messaging. New York: Bantam Books, 2002.

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