Semantic Scholar Open Access 2002 1304 sitasi

Kernel Methods for Relation Extraction

D. Zelenko Chinatsu Aone A. Richardella

Lihat Sumber DOI

Abstrak

We present an application of kernel methods to extracting relations from unstructured natural language sources. We introduce kernels defined over shallow parse representations of text, and design efficient algorithms for computing the kernels. We use the devised kernels in conjunction with Support Vector Machine and Voted Perceptron learning algorithms for the task of extracting person-affiliation and organization-location relations from text. We experimentally evaluate the proposed methods and compare them with feature-based learning algorithms, with promising results.

Topik & Kata Kunci

Computer Science Mathematics

Penulis (3)

D. Zelenko

Chinatsu Aone

A. Richardella

Format Sitasi

APA MLA BibTeX

Zelenko, D., Aone, C., Richardella, A. (2002). Kernel Methods for Relation Extraction. https://doi.org/10.3115/1118693.1118703

Akses Cepat

Lihat di Sumber doi.org/10.3115/1118693.1118703

Informasi Jurnal

Tahun Terbit: 2002
Bahasa: en
Total Sitasi: 1304×
Sumber Database: Semantic Scholar
DOI: 10.3115/1118693.1118703
Akses: Open Access ✓