Institute of Cognitive Science, University of Colorado.
Cogn Sci. 2005 Mar 4;29(2):145-93. doi: 10.1207/s15516709cog0000_9.
The syntagmatic paradigmatic model is a distributed, memory-based account of verbal processing. Built on a Bayesian interpretation of string edit theory, it characterizes the control of verbal cognition as the retrieval of sets of syntagmatic and paradigmatic constraints from sequential and relational long-term memory and the resolution of these constraints in working memory. Lexical information is extracted directly from text using a version of the expectation maximization algorithm. In this article, the model is described and then illustrated on a number of phenomena, including sentence processing, semantic categorization and rating, short-term serial recall, and analogical and logical inference. Subsequently, the model is used to answer questions about a corpus of tennis news articles taken from the Internet. The model's success demonstrates that it is possible to extract propositional information from naturally occurring text without employing a grammar, defining a set of heuristics, or specifying a priori a set of semantic roles.
组合-聚合模型是一种分布式的、基于记忆的言语处理理论。它以字符串编辑理论的贝叶斯解释为基础,将言语认知的控制描述为从序列和关系的长期记忆中检索组合-聚合约束集,并在工作记忆中解决这些约束。词汇信息是使用期望最大化算法的一个版本从文本中直接提取的。在本文中,该模型被描述,然后在许多现象上进行了说明,包括句子处理、语义分类和评分、短期序列回忆、类比和逻辑推理。随后,该模型被用于回答从互联网上获取的一组网球新闻文章的问题。该模型的成功证明了,无需使用语法、定义一组启发式规则或预先指定一组语义角色,就可以从自然语言文本中提取命题信息。