Results 61 to 70 of about 48,760 (297)

Interpretable Research Interest Shift Detection with Temporal Heterogeneous Graphs [PDF]

, 2023
Researchers dedicate themselves to research problems they are interested in and often have evolving research interests in their academic careers. The study of research interest shift detection can help to find facts relevant to scientific training paths,
Gao, Xin, Zhang, Chuxu, Zhang, Xiangliang, Yang, Qiang, Ma, Changsheng, Zhang, Qiannan   +5 more
core   +1 more source

A Temporal Knowledge Graph Embedding Model Based on Variable Translation

Tsinghua Science and Technology
Knowledge representation learning (KRL) aims to encode entities and relationships in various knowledge graphs into low-dimensional continuous vectors. It is popularly used in knowledge graph completion (or link prediction) tasks.
Yadan Han, Guangquan Lu, Shichao Zhang, Liang Zhang, Cuifang Zou, Guoqiu Wen   +5 more
doaj   +1 more source

Learning multi-graph structure for Temporal Knowledge Graph reasoning

Expert Systems with Applications
Temporal Knowledge Graph (TKG) reasoning that forecasts future events based on historical snapshots distributed over timestamps is denoted as extrapolation and has gained significant attention. Owing to its extreme versatility and variation in spatial and temporal correlations, TKG reasoning presents a challenging task, demanding efficient capture of ...
Jinchuan Zhang, Bei Hui, Chong Mu, Ling Tian   +3 more
openaire   +2 more sources

NFDI MatWerk Ontology (MWO): A BFO‐Compliant Ontology for Research Data Management in Materials Science and Engineering

Advanced Engineering Materials, EarlyView.
This article presents the NFDI‐MatWerk Ontology (MWO), a Basic Formal Ontology‐based framework for interoperable research data management in materials science and engineering (MSE). Covering consortium structures, research data management resources, services, and instruments, MWO enables semantic integration, Findable, Accessible, Interoperable, and ...
Hossein Beygi Nasrabadi, Ebrahim Norouzi, Kostiantyn Hubaiev, Jörg Waitelonis, Harald Sack   +4 more
wiley   +1 more source

Optimal temporal planning using the plangraph framework [PDF]

, 2007
The past few years have seen a rapid development in AI Planning and Scheduling. Many algorithms and techniques have been studied and improved to deal with more complex and difficult planning domains.
Dinh, Tien Ba
core  

Is an Apple an Orange? A Large Language Model Benchmark for Candidate Term Extraction and Subclass Decisions Against Upper Ontologies in Engineering and Materials Science

Advanced Engineering Materials, EarlyView.
Building machine‐readable vocabularies for materials science is slow, expert‐driven work. This study benchmarks 13 large language models on two of its first steps: finding candidate terms in engineering articles and deciding where they belong in a class hierarchy.
Thomas Bjarsch, Maximilian Holland, Klaus Drechsler, Johannes Schilp   +3 more
wiley   +1 more source

Enterprise model verification and validation : an approach [PDF]

, 2003
This article presents a verification and validation approach which is used here in order to complete the classical tool box the industrial user may utilize in enterprise modeling and integration domain. This approach, which has been defined independently
Chapurlat, Vincent, Kamsu-Foguem, Bernard, Prunet, François   +2 more
core   +1 more source

DigiChrom: A Domain Ontology for Semantic Representation of Trivalent Chromium Platings and Its Large Language Model‐Based Alignment With Multiple Mid‐Level Ontologies

Advanced Engineering Materials, EarlyView.
Digitalizing electroplating requires both domain knowledge and interoperability. This work introduces PlatOn, a domain ontology for trivalent chromium plating and coating characterization, and a hybrid pipeline that aligns it to a mid‐level reference ontology by combining eight similarity metrics with language model reasoning. Expert‐validated mappings
Janik Harter, Elena Garcia Trelles, Christoph Schweizer, Thomas Seifert, Christoph Baumer, Mahmoud Elkady, Katja Feige, Daniel Grimme, Edgar Hoffmann, Andreas Waibel, Anke Walter   +10 more
wiley   +1 more source

Temporal Knowledge Graph Completion using a Linear Temporal Regularizer and Multivector Embeddings [PDF]

, 2021
S.2569-2578Representation learning approaches for knowledge graphs have been mostly designed for static data. However, many knowledge graphs involve evolving data, e.g., the fact (The President of the United States is Barack Obama) is valid only from ...
Yung-Yu Chen, Mojtaba Nayyeri, Chen, Yung-Yu, Jens Lehmann, Xu, Chengjin, Nayyeri, Mojtaba, Lehmann, Jens, Chengjin Xu   +7 more
core   +1 more source

Learning Temporal Knowledge Graphs via Time-Sensitive Graph Attention

IEEE Access
Embedding-based graph representation learning methods have shown strong performance on knowledge graphs (KGs), but most are designed for static settings and struggle to model temporal dynamics.
Jinqing Shen, Chengjin Xu, Yingqi Liu, Xuhui Jiang, Jiaming Li, Zhenxin Huang, Jens Lehmann, Xuesong Chen   +7 more
doaj   +1 more source