Automatic Indexing And Abstracting Of Document Texts

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Automatic Indexing And Abstracting Of Document Texts

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Author : Marie-Francine Moens
language : en
Publisher: Springer
Release Date : 2013-03-12

Automatic Indexing And Abstracting Of Document Texts written by Marie-Francine Moens and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-12 with Computers categories.

Automatic Indexing and Abstracting of Document Texts summarizes the latest techniques of automatic indexing and abstracting, and the results of their application. It also places the techniques in the context of the study of text, manual indexing and abstracting, and the use of the indexing descriptions and abstracts in systems that select documents or information from large collections. Important sections of the book consider the development of new techniques for indexing and abstracting. The techniques involve the following: using text grammars, learning of the themes of the texts including the identification of representative sentences or paragraphs by means of adequate cluster algorithms, and learning of classification patterns of texts. In addition, the book is an attempt to illuminate new avenues for future research. Automatic Indexing and Abstracting of Document Texts is an excellent reference for researchers and professionals working in the field of content management and information retrieval.

Automatic Indexing And Abstracting Of Document Texts

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Author : Marie-Francine Moens
language : en
Publisher: Springer Science & Business Media
Release Date : 2005-12-27

Automatic Indexing And Abstracting Of Document Texts written by Marie-Francine Moens and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-12-27 with Computers categories.

Automatic Indexing and Abstracting of Document Texts summarizes the latest techniques of automatic indexing and abstracting, and the results of their application. It also places the techniques in the context of the study of text, manual indexing and abstracting, and the use of the indexing descriptions and abstracts in systems that select documents or information from large collections. Important sections of the book consider the development of new techniques for indexing and abstracting. The techniques involve the following: using text grammars, learning of the themes of the texts including the identification of representative sentences or paragraphs by means of adequate cluster algorithms, and learning of classification patterns of texts. In addition, the book is an attempt to illuminate new avenues for future research. Automatic Indexing and Abstracting of Document Texts is an excellent reference for researchers and professionals working in the field of content management and information retrieval.

Automatic Indexing

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Author : Mary Elizabeth Stevens
language : en
Publisher:
Release Date : 1965

Automatic Indexing written by Mary Elizabeth Stevens and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1965 with Automatic indexing categories.

Automatic Text Summarization

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Author : Juan-Manuel Torres-Moreno
language : en
Publisher: John Wiley & Sons
Release Date : 2014-11-10

Automatic Text Summarization written by Juan-Manuel Torres-Moreno and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-10 with Computers categories.

Textual information in the form of digital documents quickly accumulates to create huge amounts of data. The majority of these documents are unstructured: it is unrestricted text and has not been organized into traditional databases. Processing documents is therefore a perfunctory task, mostly due to a lack of standards. It has thus become extremely difficult to implement automatic text analysis tasks. Automatic Text Summarization (ATS), by condensing the text while maintaining relevant information, can help to process this ever-increasing, difficult-to-handle, mass of information. This book examines the motivations and different algorithms for ATS. The author presents the recent state of the art before describing the main problems of ATS, as well as the difficulties and solutions provided by the community. The book provides recent advances in ATS, as well as current applications and trends. The approaches are statistical, linguistic and symbolic. Several examples are also included in order to clarify the theoretical concepts.

Indexing And Classification

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Author : Winifred F. Desmond
language : en
Publisher: Oak Ridge, Tenn. : Oak Ridge National Laboratory
Release Date : 1966

Indexing And Classification written by Winifred F. Desmond and has been published by Oak Ridge, Tenn. : Oak Ridge National Laboratory this book supported file pdf, txt, epub, kindle and other format this book has been release on 1966 with Abstracting and indexing categories.

R Mining Spatial Text Web And Social Media Data

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Author : Bater Makhabel
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-06-19

R Mining Spatial Text Web And Social Media Data written by Bater Makhabel and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-06-19 with Computers categories.

Create data mining algorithms About This Book Develop a strong strategy to solve predictive modeling problems using the most popular data mining algorithms Real-world case studies will take you from novice to intermediate to apply data mining techniques Deploy cutting-edge sentiment analysis techniques to real-world social media data using R Who This Book Is For This Learning Path is for R developers who are looking to making a career in data analysis or data mining. Those who come across data mining problems of different complexities from web, text, numerical, political, and social media domains will find all information in this single learning path. What You Will Learn Discover how to manipulate data in R Get to know top classification algorithms written in R Explore solutions written in R based on R Hadoop projects Apply data management skills in handling large data sets Acquire knowledge about neural network concepts and their applications in data mining Create predictive models for classification, prediction, and recommendation Use various libraries on R CRAN for data mining Discover more about data potential, the pitfalls, and inferencial gotchas Gain an insight into the concepts of supervised and unsupervised learning Delve into exploratory data analysis Understand the minute details of sentiment analysis In Detail Data mining is the first step to understanding data and making sense of heaps of data. Properly mined data forms the basis of all data analysis and computing performed on it. This learning path will take you from the very basics of data mining to advanced data mining techniques, and will end up with a specialized branch of data mining—social media mining. You will learn how to manipulate data with R using code snippets and how to mine frequent patterns, association, and correlation while working with R programs. You will discover how to write code for various predication models, stream data, and time-series data. You will also be introduced to solutions written in R based on R Hadoop projects. Now that you are comfortable with data mining with R, you will move on to implementing your knowledge with the help of end-to-end data mining projects. You will learn how to apply different mining concepts to various statistical and data applications in a wide range of fields. At this stage, you will be able to complete complex data mining cases and handle any issues you might encounter during projects. After this, you will gain hands-on experience of generating insights from social media data. You will get detailed instructions on how to obtain, process, and analyze a variety of socially-generated data while providing a theoretical background to accurately interpret your findings. You will be shown R code and examples of data that can be used as a springboard as you get the chance to undertake your own analyses of business, social, or political data. This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products: Learning Data Mining with R by Bater Makhabel R Data Mining Blueprints by Pradeepta Mishra Social Media Mining with R by Nathan Danneman and Richard Heimann Style and approach A complete package with which will take you from the basics of data mining to advanced data mining techniques, and will end up with a specialized branch of data mining—social media mining.

Indexing And Abstracting 1977 1981

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Author : Hans H. Wellisch
language : en
Publisher: Santa Barbara, Calif. : ABC-Clio Information Services
Release Date : 1984

Indexing And Abstracting 1977 1981 written by Hans H. Wellisch and has been published by Santa Barbara, Calif. : ABC-Clio Information Services this book supported file pdf, txt, epub, kindle and other format this book has been release on 1984 with Language Arts & Disciplines categories.

Automatic Indexing From Machine Readable Abstracts Of Scientific Documents

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Author : Pranas Zunde
language : en
Publisher:
Release Date : 1966

Automatic Indexing From Machine Readable Abstracts Of Scientific Documents written by Pranas Zunde and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1966 with Abstracting and indexing services categories.

Knowledge Discovery From Legal Databases

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Author : Andrew Stranieri
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-03-30

Knowledge Discovery From Legal Databases written by Andrew Stranieri and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-03-30 with Computers categories.

Knowledge Discovery from Legal Databases is the first text to describe data mining techniques as they apply to law. Law students, legal academics and applied information technology specialists are guided thorough all phases of the knowledge discovery from databases process with clear explanations of numerous data mining algorithms including rule induction, neural networks and association rules. Throughout the text, assumptions that make data mining in law quite different to mining other data are made explicit. Issues such as the selection of commonplace cases, the use of discretion as a form of open texture, transformation using argumentation concepts and evaluation and deployment approaches are discussed at length.

Symposium On Materials Information Retrieval

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Author : United States. Air Force. Systems Command. Aeronautical Systems Division
language : en
Publisher:
Release Date : 1963

Symposium On Materials Information Retrieval written by United States. Air Force. Systems Command. Aeronautical Systems Division and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1963 with Information organization categories.

This report consists of a collection of papers presented at the Symposium on Materials Information Retrieval held in Dayton, Ohio, 28-29 November 1962. These papers in general discuss information storage, retrieval and dissemination programs of Government agencies and their contractors. Three areas are covered, namely materials information activities, general information activities and information systems research.