ICADL 2007 - LNCS 4822

Deriving Tree-Structured Network Relations in Bibliographic Databases

Alisa Kongthon and Niran Angkawattanawit

Human Language Technology Laboratory, National Electronics and Computer Technology Center (NECTEC), 112 Thailand Science Park, Phahon Yothin Rd., Klong Luang, Pathumthani, Thailand 12120
alisa.kongthon@nectec.or.th
niran.angkawattanawit@nectec.or.th

Abstract. This paper presents a new algorithm called “tree-structured networks” that can automatically construct parent-child (hierarchical structure) and sibling relationships (non-hierarchical structure) among concepts from a set of documents without use of data reduction or standard clustering techniques. The algorithm is applied to bibliographic databases such as INSPEC and EI Compendex toward the objective of enhancing research and development (R&D) management. Deriving tree-structured networks of research topics is an important goal in R&D management study. Parent-child relationships can help identify emerging areas in an existing field of research. Sibling relationships are interesting as well since they could represent interdisciplinary structures among related topical areas. Based on the initial testing on a set of publication abstracts, the proposed algorithm promises to offer richer structural information on relationships in text sources over the standard clustering techniques.

Keywords: Tree-structured networks, text mining, association rule mining, bibliographic databases, research and development management

LNCS 4822, p. 504 f.

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