IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Bridging Taxonomic Semantics to Accurate Hierarchical Classification

Bridging Taxonomic Semantics to Accurate Hierarchical Classification
View Sample PDF
Author(s): Lei Tang (Arizona State University, USA), Huan Liu (Arizona State University, USA)and Jiangping Zhang (The MITRE Corporation, USA)
Copyright: 2009
Pages: 5
Source title: Encyclopedia of Data Warehousing and Mining, Second Edition
Source Author(s)/Editor(s): John Wang (Montclair State University, USA)
DOI: 10.4018/978-1-60566-010-3.ch029

Purchase

View Bridging Taxonomic Semantics to Accurate Hierarchical Classification on the publisher's website for pricing and purchasing information.

Abstract

The unregulated and open nature of the Internet and the explosive growth of the Web create a pressing need to provide various services for content categorization. The hierarchical classification attempts to achieve both accurate classification and increased comprehensibility. It has also been shown in literature that hierarchical models outperform flat models in training efficiency, classification efficiency, and classification accuracy (Koller & Sahami, 1997; McCallum, Rosenfeld, Mitchell & Ng, 1998; Ruiz & Srinivasan ,1999; Dumais & Chen, 2000; Yang, Zhang & Kisiel, 2003; Cai & Hofmann, 2004; Liu, Yang, Wan, Zeng, Cheng & Ma, 2005). However, the quality of the taxonomy attracted little attention in past works. Actually, different taxonomies can result in differences in classification. So the quality of the taxonomy should be considered for real-world classifications. Even a semantically sound taxonomy does not necessarily lead to the intended classification performance (Tang, Zhang & Liu 2006). Therefore, it is desirable to construct or modify a hierarchy to better suit the hierarchical content classification task.

Related Content

Girija Ramdas, Irfan Naufal Umar, Nurullizam Jamiat, Nurul Azni Mhd Alkasirah. © 2024. 18 pages.
Natalia Riapina. © 2024. 29 pages.
Xinyu Chen, Wan Ahmad Jaafar Wan Yahaya. © 2024. 21 pages.
Fatema Ahmed Wali, Zahra Tammam. © 2024. 24 pages.
Su Jiayuan, Zhang Jingru. © 2024. 26 pages.
Pua Shiau Chen. © 2024. 21 pages.
Minh Tung Tran, Thu Trinh Thi, Lan Duong Hoai. © 2024. 23 pages.
Body Bottom