Text Mining with R: A Tidy Approach, Silge Julia Phd, Robinson David Phd

Автор: Michael W. Berry; Malu Castellanos
Название: Survey of Text Mining II
ISBN: 184996713X ISBN-13(EAN): 9781849967136
Издательство: Springer
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Цена: 88500.00 T
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Описание: This Second Edition explores the field of text mining. Coverage includes the use of machine learning in conjunction with natural language processing, information extraction, and algebraic/mathematical approaches to computational information retrieval.

Автор: Karen Jensen; George E. Heidorn; Stephen D. Richar
Название: Natural Language Processing: The PLNLP Approach
ISBN: 1461363896 ISBN-13(EAN): 9781461363897
Издательство: Springer
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Цена: 46570.00 T
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Описание: This technique is an example of one facet of the PLNLP approach: the use of natural language itself as a knowledge representation language -- an innovation that permits a wide variety of online text materials to be exploited as sources of semantic information.

Автор: Sholom M. Weiss; Nitin Indurkhya; Tong Zhang; Fred
Название: Text Mining
ISBN: 1441929967 ISBN-13(EAN): 9781441929969
Издательство: Springer
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Цена: 121110.00 T
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Описание: In our view, a prediction problem can be solved by the same methods, whether the data are structured - merical measurements or unstructured text. Text and documents can be transformed into measured values, such as the presence or absence of words, and the same methods that have proven successful for pred- tive data mining can be applied to text.

Автор: Jialu Liu, Jingbo Shang, Jiawei Han
Название: Phrase Mining from Massive Text and Its Applications
ISBN: 1627058982 ISBN-13(EAN): 9781627058988
Издательство: Mare Nostrum (Eurospan)
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Цена: 41580.00 T
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Описание: Investigates one promising paradigm for representing unstructured text, that is, through automatically identifying high-quality phrases from innumerable documents. This volume proposes new principles and powerful methodologies, from the scenario where a user can provide meaningful guidance to a fully automated setting through distant learning.

Автор: Dalianis
Название: Clinical Text Mining
ISBN: 3319785028 ISBN-13(EAN): 9783319785028
Издательство: Springer
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Цена: 46570.00 T
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Описание: This open access book describes the results of natural language processing and machine learning methods applied to clinical text from electronic patient records. It is divided into twelve chapters. Chapters 1-4 discuss the history and background of the original paper-based patient records, their purpose, and how they are written and structured. These initial chapters do not require any technical or medical background knowledge. The remaining eight chapters are more technical in nature and describe various medical classifications and terminologies such as ICD diagnosis codes, SNOMED CT, MeSH, UMLS, and ATC. Chapters 5-10 cover basic tools for natural language processing and information retrieval, and how to apply them to clinical text. The difference between rule-based and machine learning-based methods, as well as between supervised and unsupervised machine learning methods, are also explained. Next, ethical concerns regarding the use of sensitive patient records for research purposes are discussed, including methods for de-identifying electronic patient records and safely storing patient records. The book’s closing chapters present a number of applications in clinical text mining and summarise the lessons learned from the previous chapters.The book provides a comprehensive overview of technical issues arising in clinical text mining, and offers a valuable guide for advanced students in health informatics, computational linguistics, and information retrieval, and for researchers entering these fields.