Complex Words as Shortest Paths in the Network of Lexical Knowledge

IF 2.3 2区 心理学 Q2 PSYCHOLOGY, EXPERIMENTAL
Sergei Monakhov, Holger Diessel
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Abstract

Lexical models diverge on the question of how to represent complex words. Under the morpheme-based approach, each morpheme is treated as a separate unit, while under the word-based approach, morphological structure is derived from complex words. In this paper, we propose a new computational model of morphology that is based on graph theory and is intended to elaborate the word-based network approach. Specifically, we use a key concept of network science, the notion of shortest path, to investigate how complex words are learned, stored, and processed. The notion of shortest path refers to the task of finding the shortest or most optimal path connecting two non-adjacent nodes in a network. Building on this notion, the current study shows (i) that new complex words can be segmented into morphemes through the shortest path analysis; (ii) that attested English words tend to represent the shortest paths in the morphological network; and (iii) that novel (unattested) words receive higher acceptability ratings in experiments when they are formed along established optimal paths. The model's performance is tested in two experiments with human participants as well as against the behavioral data from the English Lexicon Project. We interpret our empirical results from the perspective of a usage-based model of grammar and argue that network science provides a powerful tool for analyzing language structure.

Abstract Image

复杂词是词汇知识网络中的最短路径
词法模型在如何表示复杂词的问题上存在分歧。在基于词素的方法中,每个词素都被视为一个独立的单元,而在基于词的方法中,词素结构则来自复杂的词。在本文中,我们基于图论提出了一种新的形态学计算模型,旨在阐述基于词的网络方法。具体来说,我们使用网络科学的一个关键概念--最短路径概念--来研究复杂词是如何学习、存储和处理的。最短路径的概念是指找到连接网络中两个不相邻节点的最短或最优路径。基于这一概念,目前的研究表明:(i) 通过最短路径分析,可以将复杂的新词分割成词素;(ii) 已被证实的英语词往往代表词素网络中的最短路径;(iii) 当新词(未被证实的)沿着已建立的最优路径形成时,它们在实验中会获得更高的可接受性评分。该模型的性能在两个以人类参与者为对象的实验中进行了测试,并与英语词典项目的行为数据进行了对比。我们从基于用法的语法模型的角度解释了我们的实证结果,并认为网络科学为分析语言结构提供了强有力的工具。
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来源期刊
Cognitive Science
Cognitive Science PSYCHOLOGY, EXPERIMENTAL-
CiteScore
4.10
自引率
8.00%
发文量
139
期刊介绍: Cognitive Science publishes articles in all areas of cognitive science, covering such topics as knowledge representation, inference, memory processes, learning, problem solving, planning, perception, natural language understanding, connectionism, brain theory, motor control, intentional systems, and other areas of interdisciplinary concern. Highest priority is given to research reports that are specifically written for a multidisciplinary audience. The audience is primarily researchers in cognitive science and its associated fields, including anthropologists, education researchers, psychologists, philosophers, linguists, computer scientists, neuroscientists, and roboticists.
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