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Condition: As New. Unread book in perfect condition.
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Hardcover. Condition: Brand New. 114 pages. 9.45x6.61x0.51 inches. In Stock.
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Condition: New.
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Automated Taxonomy Discovery and Exploration (Synthesis Lectures on Data Mining and Knowledge Discovery)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
£ 55.92
£ 11.98 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. In.
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Condition: New. 1st ed. 2022 edition NO-PA16APR2015-KAP.
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Automated Taxonomy Discovery and Exploration
Language: English
Published by Springer-Nature New York Inc, 2023
ISBN 10: 3031114078 ISBN 13: 9783031114076
Paperback. Condition: Brand New. 114 pages. 9.44x6.62x0.24 inches. In Stock.
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Hardcover. Condition: Brand New. 114 pages. 9.45x6.61x0.51 inches. In Stock.
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Condition: Brand New. New. US edition. Print on demand title. Delivery takes 20-25 days.
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Condition: Brand New. New. US edition. Print on demand title. Delivery takes 20-25 days.
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Condition: New. Print on Demand.
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Condition: New. Print on Demand pp. 116.
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Condition: New. PRINT ON DEMAND.
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Condition: New. PRINT ON DEMAND pp. 116.
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Automated Taxonomy Discovery and Exploration
Language: English
Published by Springer, Berlin|Springer International Publishing|Springer, 2022
ISBN 10: 3031114043 ISBN 13: 9783031114045
Gebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book provides a principled data-driven framework that progressively constructs, enriches, and applies taxonomies without leveraging massive human annotated data. Traditionally, people construct domain-specific taxonomies by extensive manual curations, .
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Automated Taxonomy Discovery and Exploration
Language: English
Published by Springer, Berlin|Springer International Publishing|Springer, 2023
ISBN 10: 3031114078 ISBN 13: 9783031114076
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book provides a principled data-driven framework that progressively constructs, enriches, and applies taxonomies without leveraging massive human annotated data. Traditionally, people construct domain-specific taxonomies by extensive manual curations, .
