Vassiliades, Alexandros; Patkos, Theodore; Efthymiou, Vasilis; Bikakis, Antonis; Bassiliades, Nick; Plexousakis, Dimitris; (2024) Extraction of object-action and object-state associations from Knowledge Graphs. Journal of Web Semantics , Article 100816. 10.1016/j.websem.2024.100816.

Preview

Text Extraction_of_Object_Action_and_Object_State_Associations_from_Knowledge_Graphs.pdf - Published Version Download (916kB) | Preview

Abstract

Infusing autonomous artificial systems with knowledge about the physical world they inhabit is a critical and long-held aim for the Artificial Intelligence community. Training systems with relevant data is a typical approach; however, finding the data required is not always possible, especially when much of this knowledge is commonsense. In this paper, we present a comparison of topology-based and semantics-based methods for extracting information about object-action and object-state association relations from knowledge graphs, such as ConceptNet, WordNet, ATOMIC, YAGO, WebChild and DBpedia. Moreover, we propose a novel method for extracting information about object-action and object-state associations from knowledge graphs. Our method is composed of a set of techniques for locating, enriching, evaluating, cleaning and exposing knowledge from such resources, relying on semantic similarity methods. Some important aspects of our method are the flexibility in deciding how to deal with the noise that exists in the data, and the capability to determine the importance of a path through training, rather than through manual annotation.

Download activity - last month

Export as JSONCSVXML

Download activity - last 12 months

Export as JSONCSVXML

Downloads by country - last 12 months

Export as XMLCSVJSON

Archive Staff Only

View Item