Results 21 to 30 of about 1,055,752 (313)
Conversational Ontology Alignment with ChatGPT [PDF]
OM@ISWC, 2023 This study evaluates the applicability and efficiency of ChatGPT for ontology alignment using a naive approach. ChatGPT's output is compared to the results of the Ontology Alignment Evaluation Initiative 2022 campaign using conference track ontologies ...
Sanaz Saki Norouzi +2 more
semanticscholar +1 more source
Truveta Mapper: A Zero-shot Ontology Alignment Framework [PDF]
OM@ISWC, 2023 In this paper, a new perspective is suggested for unsupervised Ontology Matching (OM) or Ontology Alignment (OA) by treating it as a translation task.
Mariyam Amir +6 more
semanticscholar +1 more source
Matching sensor ontologies with unsupervised neural network with competitive learning [PDF]
PeerJ Computer Science, 2021 Sensor ontologies formally model the core concepts in the sensor domain and their relationships, which facilitates the trusted communication and collaboration of Artificial Intelligence of Things (AIoT).
Xingsi Xue, Haolin Wang, Wenyu Liu
doaj +2 more sources
EventOA: An Event Ontology Alignment Benchmark Based on FrameNet and Wikidata
Annual Meeting of the Association for Computational Linguistics, 2023 Event ontology provides a shared and formal specification about what happens in the real world and can benefit many natural language understanding tasks.
Shaoru Guo +5 more
semanticscholar +1 more source
Optimizing Ontology Alignment through Linkage Learning on Entity Correspondences
Complex, 2021 Data heterogeneity is the obstacle for the resource sharing on Semantic Web (SW), and ontology is regarded as a solution to this problem. However, since different ontologies are constructed and maintained independently, there also exists the ...
Xingsi Xue +5 more
semanticscholar +1 more source
Wuhan University Journal of Natural Sciences, 2022 Ontology alignment is an essential and complex task to integrate heterogeneous ontology. The meta-heuristic algorithm has proven to be an effective method for ontology alignment.
Zhaoming Lv, Rong Peng
semanticscholar +1 more source
Matching Transportation Ontologies with Word2Vec and Alignment Extraction Algorithm
Journal of Advanced Transportation, 2021 The development of intelligent transportation systems (ITSs) faces the challenge of integrating data from multiple unrelated sources. As one of the core technologies of knowledge integration in ITS, an ontology typically provides a normative definition ...
Xingsi Xue +5 more
doaj +1 more source
Matching heterogeneous ontologies with adaptive evolutionary algorithm
Connection Science, 2022 An ontology provides a formal description on the domain concepts and their relationships. Due to the subjectivity of ontology engineers, one concept might be expressed in various ways, yielding the so-called ontology heterogeneity problem, and ontology ...
Xingsi Xue +4 more
doaj +1 more source
VeeAlign: Multifaceted Context Representation Using Dual Attention for Ontology Alignment [PDF]
Conference on Empirical Methods in Natural Language Processing, 2020 Ontology Alignment is an important research problem applied to various fields such as data integration, data transfer, data preparation, etc. State-of-the-art (SOTA) Ontology Alignment systems typically use naive domain-dependent approaches with ...
Vivek Iyer, A. Agarwal, Harshit Kumar
semanticscholar +1 more source
FOntCell: Fusion of Ontologies of Cells
Frontiers in Cell and Developmental Biology, 2021 High-throughput cell-data technologies such as single-cell RNA-seq create a demand for algorithms for automatic cell classification and characterization. There exist several cell classification ontologies with complementary information.
Javier Cabau-Laporta +10 more
doaj +1 more source