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008			221119s2022 sz | s |||| 0|eng d
020			_a9783030850852
024	7		_a10.1007/978-3-030-85085-2 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQA76.9.D343 _b2022 EB
100	1		_aLamba, Manika, _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9685381 _d1992-
245	1	0	_aText Mining for Information Professionals : _ban Uncharted Territory _cby Manika Lamba, Margam Madhusudhan
250			_aFirst edition 2022
264		1	_aCham _bSpringer International Publising _c2022
300			_a1 recurso en línea (XVI, 356 páginas) _b164 ilustraciones, 139 ilustraciones a color
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
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. .
988			_aSpringer_Computer_2022
650		7	_2embne _9162648 _aData mining
650		7	_2embne _9147823 _aRecuperación de la información
700	1		_aMadhusudhan M. _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9685382 _d1970- _q(Margam),
776	0	8	_iPrinted edition: _z9783030850845
776	0	8	_iPrinted edition: _z9783030850869
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-85085-2 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b11/2022 _dz _eIG _zSI