概念原语消除的研究:INGEST嵌入PTRANS

IF 2.4 3区 心理学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Jamie C. Macbeth, Alexis Kilayko
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引用次数: 0

摘要

在认知系统和认知语言学中,原始分解系统试图通过将事物分解为概念构建块来解释认知现象,并为系统提供丰富而灵活的表示。一个典型的例子是尚克-明斯基概念依赖跨框架系统,该系统致力于保持原语的数量较少,并允许它们以复杂的方式组合在一起,以表示意义、知识和动态情景记忆。出于保持原语集较小的愿望,本文描述了消除概念依赖INGEST原语的努力,并通过组合CD PTRANS原语和CD的包含表示来重新构建其用途。该实现是在Babel中执行的,Babel是一个自动释义生成系统,它生成CD结构的英文实现,并已用于多个自然语言理解和故事理解系统。该实现将用于为INGEST原语选择词义的判别网与用于PTRANS原语的判别网结合起来。一旦实现完成,我们还使用新的结构运行Babel来生成CD结构的释义,并确定在原始的重新表达努力中成功的程度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A study of conceptual primitive elimination: Embedding INGEST into PTRANS
In cognitive systems and cognitive linguistics, primitive decomposition systems attempt to explain cognitive phenomena by breaking things down into conceptual building blocks and provide rich and flexible representations for systems. A prime example is the Schank–Minsky Conceptual Dependency Trans-frames system, which maintains a commitment to keeping the number of primitives small and allowing them to be combined in complex ways in representing meaning, knowledge, and dynamic episodic memory. Motivated by the desire to keep the set of primitives small, this paper describes an effort to eliminate the Conceptual Dependency INGEST primitive and reconstitute its uses through combinations of the CD PTRANS primitive and CD’s representations of containment. The implementation is performed in Babel, an automated paraphrase generation system which generates English realizations of CD structures and which has been used in multiple natural language understanding and story understanding systems. The implementation combines the discrimination nets used for selecting word senses for the INGEST primitive with those for the PTRANS primitive. Once the implementation was complete, we also ran Babel using the new structures to generate paraphrases of CD structures and to determine the degree of success in our primitive re-expression endeavor.
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来源期刊
Cognitive Systems Research
Cognitive Systems Research 工程技术-计算机:人工智能
CiteScore
9.40
自引率
5.10%
发文量
40
审稿时长
>12 weeks
期刊介绍: Cognitive Systems Research is dedicated to the study of human-level cognition. As such, it welcomes papers which advance the understanding, design and applications of cognitive and intelligent systems, both natural and artificial. The journal brings together a broad community studying cognition in its many facets in vivo and in silico, across the developmental spectrum, focusing on individual capacities or on entire architectures. It aims to foster debate and integrate ideas, concepts, constructs, theories, models and techniques from across different disciplines and different perspectives on human-level cognition. The scope of interest includes the study of cognitive capacities and architectures - both brain-inspired and non-brain-inspired - and the application of cognitive systems to real-world problems as far as it offers insights relevant for the understanding of cognition. Cognitive Systems Research therefore welcomes mature and cutting-edge research approaching cognition from a systems-oriented perspective, both theoretical and empirically-informed, in the form of original manuscripts, short communications, opinion articles, systematic reviews, and topical survey articles from the fields of Cognitive Science (including Philosophy of Cognitive Science), Artificial Intelligence/Computer Science, Cognitive Robotics, Developmental Science, Psychology, and Neuroscience and Neuromorphic Engineering. Empirical studies will be considered if they are supplemented by theoretical analyses and contributions to theory development and/or computational modelling studies.
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