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Terminology saturation = detection, ...

Kosa, Victoria.

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Terminology saturation = detection, measurement and use /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Terminology saturation/ by Victoria Kosa, Vadim Ermolayev.
其他題名:	detection, measurement and use /
作者:	Kosa, Victoria.
其他作者:	Ermolayev, Vadim.
出版者:	Singapore :Springer Singapore : : 2022.,
面頁冊數:	xxii, 177 p. :ill. (some col.), digital ;24 cm.
內容註:	1. Introduction -- 2. Representativeness Challenge in Ontology Engineering -- 3. The Phenomenon of Saturation -- 4. The Structure of the Book -- 5. Related Work.
Contained By:	Springer Nature eBook
標題:	Data mining. -
電子資源:	https://doi.org/10.1007/978-981-16-8630-6
ISBN:	9789811686306

Terminology saturation = detection, measurement and use /
Kosa, Victoria.

Terminology saturationdetection, measurement and use /[electronic resource] :by Victoria Kosa, Vadim Ermolayev. - Singapore :Springer Singapore :2022. - xxii, 177 p. :ill. (some col.), digital ;24 cm. - Cognitive science and technology,2195-3996. - Cognitive science and technology..

1. Introduction -- 2. Representativeness Challenge in Ontology Engineering -- 3. The Phenomenon of Saturation -- 4. The Structure of the Book -- 5. Related Work.

This book highlights an innovative approach for extracting terminological cores from subject domain-bounded collections of professional texts. The approach is based on exploiting the phenomenon of terminological saturation. The book presents the formal framework for the method of detecting and measuring terminological saturation as a successive approximation process. It further offers the suite of the algorithms that implement the method in the software and comprehensively evaluates all the aspects of the method and possible input configurations in the experiments on synthetic and real collections of texts in several subject domains. The book demonstrates the use of the developed method and software pipeline in industrial and academic use cases. It also outlines the potential benefits of the method for the adoption in industry.

ISBN: 9789811686306

Standard No.: 10.1007/978-981-16-8630-6doiSubjects--Topical Terms:

562972
Data mining.

LC Class. No.: QA76.9.D343 / K67 2022

Dewey Class. No.: 006.312

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