ImageSchemaNet: A framester graph for embodied commonsense knowledge

IF 3 3区计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Semantic Web Pub Date : 2022-11-03 DOI:10.3233/sw-223084

Stefano De Giorgis, Aldo Gangemi, Dagmar Gromann

引用次数: 2

Abstract

Commonsense knowledge is a broad and challenging area of research which investigates our understanding of the world as well as human assumptions about reality. Deriving directly from the subjective perception of the external world, it is intrinsically intertwined with embodied cognition. Commonsense reasoning is linked to human sense-making, pattern recognition and knowledge framing abilities. This work presents a new resource that formalizes the cognitive theory of image schemas. Image schemas are dynamic conceptual building blocks originating from our sensorimotor interactions with the physical world, and enable our sense-making cognitive activity to assign coherence and structure to entities, events and situations we experience everyday. ImageSchemaNet is an ontology that aligns pre-existing resources, such as FrameNet, VerbNet, WordNet and MetaNet from the Framester hub, to image schema theory. This article describes an empirical application of ImageSchemaNet, combined with semantic parsers, on the task of annotating natural language sentences with image schemas.

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ImageSchemaNet:包含常识性知识的框架图

常识知识是一个广泛而具有挑战性的研究领域，它调查了我们对世界的理解以及人类对现实的假设。它直接来源于对外部世界的主观感知，本质上与具身认知交织在一起。常识推理与人类的理解、模式识别和知识框架能力有关。这项工作提供了一个新的资源，形式化的认知理论的意象图式。意象图式是源于我们与物理世界的感觉运动互动的动态概念构建模块，它使我们的意义形成认知活动能够为我们每天经历的实体、事件和情境分配连贯性和结构。ImageSchemaNet是一个本体，它将已有的资源(如Framester中心的FrameNet、vernet、WordNet和MetaNet)与图像图式理论结合在一起。本文描述了ImageSchemaNet结合语义解析器在用图像模式注释自然语言句子方面的经验应用。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Semantic Web COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCEC-COMPUTER SCIENCE, INFORMATION SYSTEMS

CiteScore

8.30

自引率

6.70%

发文量

期刊介绍： The journal Semantic Web – Interoperability, Usability, Applicability brings together researchers from various fields which share the vision and need for more effective and meaningful ways to share information across agents and services on the future internet and elsewhere. As such, Semantic Web technologies shall support the seamless integration of data, on-the-fly composition and interoperation of Web services, as well as more intuitive search engines. The semantics – or meaning – of information, however, cannot be defined without a context, which makes personalization, trust, and provenance core topics for Semantic Web research. New retrieval paradigms, user interfaces, and visualization techniques have to unleash the power of the Semantic Web and at the same time hide its complexity from the user. Based on this vision, the journal welcomes contributions ranging from theoretical and foundational research over methods and tools to descriptions of concrete ontologies and applications in all areas. We especially welcome papers which add a social, spatial, and temporal dimension to Semantic Web research, as well as application-oriented papers making use of formal semantics.