000 | 03634nam a22005415i 4500 | ||
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001 | 978-3-030-85085-2 | ||
003 | DE-He213 | ||
005 | 20240423125543.0 | ||
007 | cr nn 008mamaa | ||
008 | 220421s2022 sz | s |||| 0|eng d | ||
020 |
_a9783030850852 _9978-3-030-85085-2 |
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024 | 7 |
_a10.1007/978-3-030-85085-2 _2doi |
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050 | 4 | _aQA76.9.D343 | |
072 | 7 |
_aUNF _2bicssc |
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_aUYQE _2thema |
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_a006.312 _223 |
100 | 1 |
_aLamba, Manika. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
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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. |
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300 |
_aXVI, 356 p. 164 illus., 139 illus. in color. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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_atext file _bPDF _2rda |
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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 |
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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 |