Evocation: analyzing and propagating a semantic link based on free word association
Evocation: analyzing and propagating a semantic link based on free word association
复制标题
唤起：基于自由词关联分析和传播语义链接
DOI：
10.1007/s10579-013-9219-2
复制
发表时间：
2013
影响因子：
2.7
通讯作者：
Xiaojuan Ma
中科院分区：
文献类型：
--
作者：
Xiaojuan Ma
词汇-语义关系研究的目的是了解语义记忆的机制和心理词汇的组织。然而，标准的聚合关系，如“上义词”和“下义词”不能捕捉不同词性的概念之间的联系。WordNet，它组织同义词集（即，同义词集）使用这些词汇语义关系，是相当稀疏的连接。根据WordNet的统计，每个同义词集的上下义关系的传出/传入弧的平均数量为1.33。唤起度是一个概念（由一个或多个词表示）引起另一个概念的程度，它是一种新的概念间语义相关性的有向加权度量。常用的语义关系和相关性的措施似乎并不完全兼容的数据，反映概念之间的调用。它们是兼容的，但唤起捕捉更多。这项工作的目的是提供一个可靠的和可扩展的数据集的概念引起的，并唤起，其他概念，以丰富WordNet，现有的语义网络。我们建议使用消歧的自由词联想数据（对言语刺激的第一反应）来推断和收集唤起评级。WordNet旨在表征心理词汇的组织结构，心理语言学家利用词的自由联想来探索语义组织结构有助于理解。这项工作分两个阶段进行。在第一阶段，它被证实，现有的自由词联想规范可以转换成唤起数据计算。在第二阶段中，两阶段的关联-注释过程中收集的唤起数据从人类的判断进行了比较，国家的最先进的方法，表明引入自由联想可以大大提高质量的唤起数据生成。Evocation可以作为带有刻度的定向链接并入WordNet，并有利于各种自然语言处理应用程序。
Studies of lexical–semantic relations aim to understand the mechanism of semantic memory and the organization of the mental lexicon. However, standard paradigmatic relations such as “hypernym” and “hyponym” cannot capture connections among concepts from different parts of speech. WordNet, which organizes synsets (i.e., synonym sets) using these lexical–semantic relations, is rather sparse in its connectivity. According to WordNet statistics, the average number of outgoing/incoming arcs for the hypernym/hyponym relation per synset is 1.33. Evocation, defined as how much a concept (expressed by one or more words) brings to mind another, is proposed as a new directed and weighted measure for the semantic relatedness among concepts. Commonly applied semantic relations and relatedness measures do not seem to be fully compatible with data that reflect evocations among concepts. They are compatible but evocation captures MORE. This work aims to provide a reliable and extendable dataset of concepts evoked by, and evoking, other concepts to enrich WordNet, the existing semantic network. We propose the use of disambiguated free word association data (first responses to verbal stimuli) to infer and collect evocation ratings. WordNet aims to represent the organization of mental lexicon, and free word association which has been used by psycholinguists to explore semantic organization can contribute to the understanding. This work was carried out in two phases. In the first phase, it was confirmed that existing free word association norms can be converted into evocation data computationally. In the second phase, a two-stage association-annotation procedure of collecting evocation data from human judgment was compared to the state-of-the-art method, showing that introducing free association can greatly improve the quality of the evocation data generated. Evocation can be incorporated into WordNet as directed links with scales, and benefits various natural language processing applications.
影响因子：
7.6
作者：
BUSS, DM
通讯作者：
BUSS, DM