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020 _a9783030850852
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024 7 _a10.1007/978-3-030-85085-2
_2doi
050 4 _aQA76.9.D343
072 7 _aUNF
_2bicssc
072 7 _aUYQE
_2bicssc
072 7 _aCOM021030
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072 7 _aUNF
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082 0 4 _a006.312
_223
100 1 _aLamba, Manika.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aText Mining for Information Professionals
_h[electronic resource] :
_bAn Uncharted Territory /
_cby Manika Lamba, Margam Madhusudhan.
250 _a1st ed. 2022.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2022.
300 _aXVI, 356 p. 164 illus., 139 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _a1. The Computational Library -- 2. Text Data and Where to Find Them? -- 3. Text Pre-Processing -- 4. Topic Modeling -- 5. Network Text Analysis -- 6. Burst Detection -- 7. Sentiment Analysis -- 8. Predictive Modeling -- 9. Information Visualization -- 10. Tools and Techniques for Text Mining and Visualization -- 11. Text Data and Mining Ethics.
520 _aThis book focuses on a basic theoretical framework dealing with the problems, solutions, and applications of text mining and its various facets in a very practical form of case studies, use cases, and stories. The book contains 11 chapters with 14 case studies showing 8 different text mining and visualization approaches, and 17 stories. In addition, both a website and a Github account are also maintained for the book. They contain the code, data, and notebooks for the case studies; a summary of all the stories shared by the librarians/faculty; and hyperlinks to open an interactive virtual RStudio/Jupyter Notebook environment. The interactive virtual environment runs case studies based on the R programming language for hands-on practice in the cloud without installing any software. From understanding different types and forms of data to case studies showing the application of each text mining approaches on data retrieved from various resources, this book is a must-read for all library professionals interested in text mining and its application in libraries. Additionally, this book will also be helpful to archivists, digital curators, or any other humanities and social science professionals who want to understand the basic theory behind text data, text mining, and various tools and techniques available to solve and visualize their research problems. .
650 0 _aData mining.
650 0 _aLibrary science.
650 0 _aApplication software.
650 1 4 _aData Mining and Knowledge Discovery.
650 2 4 _aLibrary Science.
650 2 4 _aComputer and Information Systems Applications.
700 1 _aMadhusudhan, Margam.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783030850845
776 0 8 _iPrinted edition:
_z9783030850869
856 4 0 _uhttps://doi.org/10.1007/978-3-030-85085-2
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
942 _cSPRINGER
999 _c179213
_d179213