Journal article
A Latent Semantic Indexing-based approach to multilingual document clustering
Decision Support Systems, v 45(3), pp 606-620
2008
Abstract
The creation and deployment of knowledge repositories for managing, sharing, and reusing tacit knowledge within an organization has emerged as a prevalent approach in current knowledge management practices. A knowledge repository typically contains vast amounts of formal knowledge elements, which generally are available as documents. To facilitate users' navigation of documents within a knowledge repository, knowledge maps, often created by document clustering techniques, represent an appealing and promising approach. Various document clustering techniques have been proposed in the literature, but most deal with monolingual documents (i.e., written in the same language). However, as a result of increased globalization and advances in Internet technology, an organization often maintains documents in different languages in its knowledge repositories, which necessitates multilingual document clustering (MLDC) to create organizational knowledge maps. Motivated by the significance of this demand, this study designs a Latent Semantic Indexing (LSI)-based MLDC technique capable of generating knowledge maps (i.e., document clusters) from multilingual documents. The empirical evaluation results show that the proposed LSI-based MLDC technique achieves satisfactory clustering effectiveness, measured by both cluster recall and cluster precision, and is capable of maintaining a good balance between monolingual and cross-lingual clustering effectiveness when clustering a multilingual document corpus.
Metrics
Details
- Title
- A Latent Semantic Indexing-based approach to multilingual document clustering
- Creators
- Chih-Ping Wei - Institute of Technology Management, College of Technology Management, National Tsing Hua University, Hsinchu, Taiwan, ROCChristopher C Yang - Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, Shatin, N.T., Hong KongChia-Min Lin - Openfind Information Technology Inc., 4F, No. 222, Sec. 2, Nan-Chang Rd., Taipei, Taiwan, ROC
- Publication Details
- Decision Support Systems, v 45(3), pp 606-620
- Publisher
- Elsevier
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Information Science
- Web of Science ID
- WOS:000257566900020
- Scopus ID
- 2-s2.0-44949210319
- Other Identifier
- 991014878367404721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Computer Science, Information Systems
- Operations Research & Management Science