MINING MULTILINGUAL TEXTS USING GROWING HIERARCHICAL SELF-ORGANIZING MAPS

摘要：

The WWW provides an ultimate source of information for all kinds of knowledge in various kinds of languages.There are emerging needs for searching documents in different languages, causing multilingual information retrieval an active research topic recently.The performance of such task depends on the degree of understanding for the relationships between different languages.Multilingual text mining aims at discovering interesting relationships between different languages.In this work, we applied the growing hierarchical self-organizing map model to cluster multilingual text documents and find the relationships between two languages.We use a set of parallel corpora to train the map and apply a discovering process to identify the semantic groups and hierarchical structures of keywords for these languages.The discovered knowledge can then be applied to tasks such as multilingual information retrieval and automatic multilingual thesaurus construction.

关键词： Multilingual text mining Growing hierarchical self-organizing Map Multilingual information retrieval

作者: HSIN-CHANG YANG DING-WEN CHEN CHUNG-HONG LEE

作者单位: Department of Information Management, National University of Kaohsiung, Kaohsiung, Taiwan, ROC Department of Information Management, Chang Jung Christian University, Tainan, Taiwan, ROC Department of Electrical Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung,

会议类型: 国际会议

会议名称: 2007 International Conference on Machine Learning and Cybernetics(IEEE第六届机器学习与控制论国际会议)

会议地点: 香港

会议语种:英文

页码: 2263-2268

在线出版日期: 2007-08-19（万方平台首次上网日期，不代表论文的发表时间）