Automatic Keyword Extraction: Combining Machine Learning and Natural Language Processing

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9783639038552: Automatic Keyword Extraction: Combining Machine Learning and Natural Language Processing

In order to make further progress in the field of automatic text retrieval, approaches extending current standard full text indexing methods need to be investigated. This book advocates keyword indexing as one such feasible approach. More specifically it discusses the development of an algorithm for automatic keyword extraction and presents anumber of experiments in which the performance of the algorithm is incrementally improved. Automatic keyword extraction is the task of automatically selecting a small set of terms describing the content of a single document. That a keyword is extracted means that it is present verbatim in the document to which it is assigned. The approach taken is that of supervised machine learning, that is, prediction models are constructed from documents with known keywords. The work presented is linguistically oriented in the sense that the output from natural language processing tools is a considerable factor both for the pre-processing of the data, as well as for the performance of the prediction models. This is a book for anybody in the field of language technology who is interested in the applicable but challenging area of automatic keyword indexing.

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About the Author:

Anette Hulth, PhD: Studied linguistics and computer and systems sciences at Stockholm University, Sweden. Currently holds a position at the Swedish Institute for Infectious Disease Control.

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Hulth, Anette
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Book Description Book Condition: New. Publisher/Verlag: VDM Verlag Dr. Müller | Combining Machine Learning and Natural Language Processing | In order to make further progress in the field of automatic text retrieval, approaches extending current standard full text indexing methods need to be investigated. This book advocates keyword indexing as one such feasible approach. More specifically it discusses the development of an algorithm for automatic keyword extraction and presents a number of experiments in which the performance of the algorithm is incrementally improved. Automatickey word extraction is the task of automatically selecting a small set of terms describing the content of a single document. That a keyword is extracted means that it is present verbatim in the document to which it is assigned. The approach taken is that of supervised machine learning, that is, prediction models are constructed from documents with known keywords. The work presented is linguistically oriented in the sense that the output fromnatural language processing tools is a considerable factor both forthe pre-processing of the data, as well as for the performance of the prediction models. This is a book for anybody in the field of language technology who is interested in the applicable but challenging area of automatic keyword indexing. | Format: Paperback | Language/Sprache: english | 150 gr | 100 pp. Bookseller Inventory # K9783639038552

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Book Description VDM Verlag Dr. Mueller e.K., Germany, 2008. Paperback. Book Condition: New. Language: English . Brand New Book ***** Print on Demand *****.In order to make further progress in the field of automatic text retrieval, approaches extending current standard full text indexing methods need to be investigated. This book advocates keyword indexing as one such feasible approach. More specifically it discusses the development of an algorithm for automatic keyword extraction and presents a number of experiments in which the performance of the algorithm is incrementally improved. Automatic keyword extraction is the task of automatically selecting a small set of terms describing the content of a single document. That a keyword is extracted means that it is present verbatim in the document to which it is assigned. The approach taken is that of supervised machine learning, that is, prediction models are constructed from documents with known keywords. The work presented is linguistically oriented in the sense that the output from natural language processing tools is a considerable factor both for the pre-processing of the data, as well as for the performance of the prediction models. This is a book for anybody in the field of language technology who is interested in the applicable but challenging area of automatic keyword indexing. Bookseller Inventory # AAV9783639038552

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Book Description VDM Verlag. Paperback. Book Condition: New. Paperback. 104 pages. Dimensions: 8.5in. x 5.9in. x 0.2in.In order to make further progress in the field of automatic text retrieval, approaches extending current standard full text indexing methods need to be investigated. This book advocates keyword indexing as one such feasible approach. More specifically it discusses the development of an algorithm for automatic keyword extraction and presents anumber of experiments in which the performance of the algorithm is incrementally improved. Automatic keyword extraction is the task of automatically selecting a small set of terms describing the content of a single document. That a keyword is extracted means that it is present verbatim in the document to which it is assigned. The approach taken is that of supervised machine learning, that is, prediction models are constructed from documents with known keywords. The work presented is linguistically oriented in the sense that the output from natural language processing tools is a considerable factor both for the pre-processing of the data, as well as for the performance of the prediction models. This is a book for anybody in the field of language technology who is interested in the applicable but challenging area of automatic keyword indexing. This item ships from multiple locations. Your book may arrive from Roseburg,OR, La Vergne,TN. Paperback. Bookseller Inventory # 9783639038552

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