http://dx.doi.org/10.6129/CJP.2009.5104.02
Chinese Journal of Psychology, 51(4), 2009，415-435

陳明蕾（國立中央大學學習與教學研究所）；王學誠（麻州州立大學波士頓校區資訊科學學系）；柯華葳（國立中央大學學習與教學研究所）

摘要

近年來，運用大型語料為基礎，進行比對及描繪詞彙間的語意關係，是心理語言學中新興的研究取向。本文採用潛在語意分析技術，建立一個能表徵中文詞彙間語意關聯性的語意空間。此一語意空間的特色是可以將隱藏在詞彙背後的語意關連性呈現出來，而且也能以向量的方式，進行詞彙與句子、詞彙與文件之間語意關聯性的比對。實驗結果顯示，以潛在語意分析技術所建置的中文語意空間，能反應中文讀者內在心理詞彙表徵間之語意關聯性。

關鍵詞：語意空間、語意關聯性、潛在語意分析

The Construction and Validation of Chinese Semantic Space by Using Latent Semantic Analysis

Ming-Lei Chen（Institute of Learning and Instruction, National Central University）；Hsueh-Cheng Wang（Department of Computer Science, University of Massachusetts at Boston, MA.）；Hwa-Wei Ko（Institute of Learning and Instruction, National Central University）

Abstract

Recently, using corpus to create a word net is a new approach in psycholinguistic study. The present study used Latent semantic analysis (LSA) to create a Chinese semantic space. The semantic relationship between words in the Chinese semantic space was estimated by taking the dot product (cosine) between two vectors. The semantic relationship between two sentences or two documents could be estimated in the same way. The results of human data indicate that the Chinese semantic space is a valid way to represent Chinese reader’s world knowledge.

Keywords: latent semantic analysis, semantic relation, semantic space