Semantically constitutive entities in knowledge graphs

• المؤلفون الرئيسيون: CHIA, Chong Cher, TKACHENKO, Maksim, LAUW, Hady Wirawan
• التنسيق: text
• اللغة: English
• منشور في: Institutional Knowledge at Singapore Management University 2023
• الموضوعات: embeddings; knowledge graph; semantically constitutive; Artificial Intelligence and Robotics; Databases and Information Systems
• الوصول للمادة أونلاين: https://ink.library.smu.edu.sg/sis_research/8312; https://ink.library.smu.edu.sg/context/sis_research/article/9315/viewcontent/dexa23.pdf
• المؤسسة: Singapore Management University

Knowledge graphs are repositories of facts about a world. In this work, we seek to distill the set of entities or nodes in a knowledge graph into a specified number of constitutive nodes, whose embeddings would be retained. Intuitively, the remaining accessory nodes could have their original embeddings “forgotten”, and yet reconstitutable from those of the retained constitutive nodes. The constitutive nodes thus represent the semantically constitutive entities, which retain the core semantics of the knowledge graph. We propose a formulation as well as algorithmic solutions to minimize the reconstitution errors. The derived constitutive nodes are validated empirically both in quantitative and qualitative means on three well-known publicly accessible knowledge graphs. Experiments show that the selected semantically constitutive entities outperform those selected based on structural properties alone.