Automated Taxonomy Discovery and Exploration (Record no. 86092)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 03955nam a22005775i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 978-3-031-11405-2 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20240730165106.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 220928s2022 sz | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9783031114052 |
| -- | 978-3-031-11405-2 |
| 082 04 - CLASSIFICATION NUMBER | |
| Call Number | 006.31 |
| 100 1# - AUTHOR NAME | |
| Author | Shen, Jiaming. |
| 245 10 - TITLE STATEMENT | |
| Title | Automated Taxonomy Discovery and Exploration |
| 250 ## - EDITION STATEMENT | |
| Edition statement | 1st ed. 2022. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | XI, 103 p. 34 illus., 31 illus. in color. |
| 490 1# - SERIES STATEMENT | |
| Series statement | Synthesis Lectures on Data Mining and Knowledge Discovery, |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Remark 2 | Introduction -- Concept Set Expansion -- Taxonomy Construction -- Taxonomy Enrichment -- Taxonomy-Guided Classification -- Conclusions. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | 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, which is time-consuming and costly. In today's information era, people are inundated with the vast amounts of text data. Despite their usefulness, people haven't yet exploited the full power of taxonomies due to the heavy curation needed for creating and maintaining them. To bridge this gap, the authors discuss automated taxonomy discovery and exploration, with an emphasis on label-efficient machine learning methods and their real-world usages. Taxonomy organizes entities and concepts in a hierarchy way. It is ubiquitous in our daily life, ranging from product taxonomies used by online retailers, topic taxonomies deployed by news outlets and social media, as well as scientific taxonomies deployed by digital libraries across various domains. When properly analyzed, these taxonomies can play a vital role for science, engineering, business intelligence, policy design, ecommerce, and more. Intuitive examples are used throughout enabling readers to grasp concepts more easily. In addition, this book: Discusses the process of creating, maintaining, and applying taxonomies via simple, easy-to-understand examples Provides a systematic review of the current research frontier of each task and discusses their real-world applications Includes supporting materials containing links to commonly used evaluation datasets and a code repository of representative algorithms. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Han, Jiawei. |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | https://doi.org/10.1007/978-3-031-11405-2 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | eBooks |
| 264 #1 - | |
| -- | Cham : |
| -- | Springer International Publishing : |
| -- | Imprint: Springer, |
| -- | 2022. |
| 336 ## - | |
| -- | text |
| -- | txt |
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| -- | computer |
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| -- | rdamedia |
| 338 ## - | |
| -- | online resource |
| -- | cr |
| -- | rdacarrier |
| 347 ## - | |
| -- | text file |
| -- | |
| -- | rda |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Machine learning. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computer science. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Information storage and retrieval systems. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Data mining. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Big data. |
| 650 14 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Machine Learning. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computer Science. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Information Storage and Retrieval. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Data Mining and Knowledge Discovery. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Big Data. |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
| -- | 2151-0075 |
| 912 ## - | |
| -- | ZDB-2-SXSC |
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