@article{MTMT:34714152,
	title = {Design Principles for Background Knowledge to Enhance Learning in Citizen Science},
	url = {https://m2.mtmt.hu/api/publication/34714152},
	isbn = {9783031280313},
	author = {Crowston, K. and Jackson, C. and Corieri, I. and Østerlund, C.},
	doi = {10.1007/978-3-031-28032-0_43},
	journal-iso = {LECT NOTES ARTIF INT},
	journal = {LECTURE NOTES IN ARTIFICIAL INTELLIGENCE},
	volume = {13972},
	unique-id = {34714152},
	issn = {0302-9743},
	year = {2023},
	pages = {563-580}
}

@article{MTMT:34534897,
	title = {Unveiling Knowledge Organization Systems’ Artifacts for Digital Agriculture with Lexical Network Analysis},
	url = {https://m2.mtmt.hu/api/publication/34534897},
	author = {Soares, F.M. and Bergier, I. and Coradini, M.C. and Ferreira, A.P.L. and Telles, M.A. and dos Santos Maculan, B.C.M. and de Cléofas Faggion Alencar, M. and Simão, V.P.M. and de Almeida, B.T. and Drucker, D.P. and Machado Vieira, M.S. and da Cruz, S.M.S.},
	doi = {10.1007/978-3-031-47112-4_28},
	journal-iso = {LECT NOTES ARTIF INT},
	journal = {LECTURE NOTES IN ARTIFICIAL INTELLIGENCE},
	volume = {14319 LNCS},
	unique-id = {34534897},
	issn = {0302-9743},
	abstract = {This article presents a bibliometric and terminological study of a corpus composed of abstracts and titles of 278 articles retrieved by a review protocol planned for surveying initiatives on building artifacts for modeling knowledge related to agricultural production systems. The original corpus comprised a 53,379-word linguistic extract filtered to 111 interconnected major terminologies by combining AntConc and VOSViewer tools. The reduced data were imported into the Gephi tool for analysis of lexical network graphs. Emergent clusters and their central terms underscore the thematic areas that prominently shape the landscape of agricultural Knowledge Organization Systems (KOS) and highlight the interplay between technological advancements, semantic enrichment, and domain-specific challenges. Our analysis of term occurrences and clusters contributes to a broader understanding of these concepts, inferring their significance, roles, and interconnections within the agricultural landscape. It also sheds light on the roles played by KOS in Digital Agriculture. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.},
	keywords = {Semantics; AGRICULTURE; Terminology; Metadata; ontologies; corpus linguistics; corpus linguistics; knowledge organization; bibliometric; Knowledge graph; Knowledge graph; Knowledge graphs; Thesauri; digital agriculture; knowledge organization systems; Thesaurus; Ontology's; KOS; Knowledge organization system (KOS); Agricultural production system; Lexical networks; Model knowledge; Semantic artifact; Semantic artifacts},
	year = {2023},
	pages = {299-311}
}

@article{MTMT:34406580,
	title = {Preface},
	url = {https://m2.mtmt.hu/api/publication/34406580},
	isbn = {978-303140246-3},
	author = {Holzer, M. and Nagy, Benedek},
	journal-iso = {LECT NOTES ARTIF INT},
	journal = {LECTURE NOTES IN ARTIFICIAL INTELLIGENCE},
	volume = {14151 LNCS},
	unique-id = {34406580},
	issn = {0302-9743},
	year = {2023},
	pages = {v-vi}
}

@article{MTMT:33857731,
	title = {Discovery of Small Signals in Big Backgrounds},
	url = {https://m2.mtmt.hu/api/publication/33857731},
	isbn = {9783031283499},
	author = {Purohit, M.V.},
	doi = {10.1007/978-3-031-28350-5_3},
	journal-iso = {LECT NOTES ARTIF INT},
	journal = {LECTURE NOTES IN ARTIFICIAL INTELLIGENCE},
	volume = {13830 LNCS},
	unique-id = {33857731},
	issn = {0302-9743},
	year = {2023},
	pages = {31-37}
}

@article{MTMT:33856740,
	title = {Trigger Detection for the sPHENIX Experiment via Bipartite Graph Networks with Set Transformer},
	url = {https://m2.mtmt.hu/api/publication/33856740},
	author = {Xuan, T. and Borca-Tasciuc, G. and Zhu, Y. and Sun, Y. and Dean, C. and Shi, Z. and Yu, D.},
	doi = {10.1007/978-3-031-26409-2_4},
	journal-iso = {LECT NOTES ARTIF INT},
	journal = {LECTURE NOTES IN ARTIFICIAL INTELLIGENCE},
	volume = {13715},
	unique-id = {33856740},
	issn = {0302-9743},
	year = {2023},
	pages = {51-67}
}

@article{MTMT:34451643,
	title = {Multi-scale Subgraph Contrastive Learning for Link Prediction},
	url = {https://m2.mtmt.hu/api/publication/34451643},
	author = {Sun, S. and Zhang, Z. and Wang, R. and Tian, H.},
	doi = {10.1007/978-3-031-21244-4_16},
	journal-iso = {LECT NOTES ARTIF INT},
	journal = {LECTURE NOTES IN ARTIFICIAL INTELLIGENCE},
	volume = {13633},
	unique-id = {34451643},
	issn = {0302-9743},
	year = {2022},
	pages = {217-223}
}

@article{MTMT:34393753,
	title = {e-Participation as Mediated Ecosystem? A Case Study on Municipalities of St. Petersburg, Russia},
	url = {https://m2.mtmt.hu/api/publication/34393753},
	author = {Misnikov, Y and Filatova, O},
	doi = {10.1007/978-3-031-22131-6_7},
	journal-iso = {LECT NOTES ARTIF INT},
	journal = {LECTURE NOTES IN ARTIFICIAL INTELLIGENCE},
	volume = {13517},
	unique-id = {34393753},
	issn = {0302-9743},
	year = {2022},
	pages = {81-96}
}

@article{MTMT:34026936,
	title = {Data Mining Methods for Analysis and Forecast of an Emerging Technology Trend: A Systematic Mapping Study from SCOPUS Papers},
	url = {https://m2.mtmt.hu/api/publication/34026936},
	author = {Viet, N.T. and Kravets, A. and Hoang, T.D.Q.},
	doi = {10.1007/978-3-030-86855-0_7},
	journal-iso = {LECT NOTES ARTIF INT},
	journal = {LECTURE NOTES IN ARTIFICIAL INTELLIGENCE},
	volume = {12948},
	unique-id = {34026936},
	issn = {0302-9743},
	year = {2021},
	pages = {81-101}
}

@article{MTMT:32488441,
	title = {OnCall Operator Scheduling for Satellites with Grover’s Algorithm},
	url = {https://m2.mtmt.hu/api/publication/32488441},
	author = {Scherer, A. and Guggemos, T. and Grundner-Culemann, S. and Pomplun, N. and Prüfer, S. and Spörl, A.},
	doi = {10.1007/978-3-030-77980-1_2},
	journal-iso = {LECT NOTES ARTIF INT},
	journal = {LECTURE NOTES IN ARTIFICIAL INTELLIGENCE},
	volume = {12747 LNCS},
	unique-id = {32488441},
	issn = {0302-9743},
	year = {2021},
	pages = {17-29}
}

@article{MTMT:33789131,
	title = {Improving Classification of Basic Spatial Audio Scenes in Binaural Recordings of Music by Deep Learning Approach},
	url = {https://m2.mtmt.hu/api/publication/33789131},
	author = {Zieliński, S.K. and Saeed K., Dvorsky J.},
	doi = {10.1007/978-3-030-47679-3_25},
	journal-iso = {LECT NOTES ARTIF INT},
	journal = {LECTURE NOTES IN ARTIFICIAL INTELLIGENCE},
	volume = {12133 LNCS},
	unique-id = {33789131},
	issn = {0302-9743},
	year = {2020},
	pages = {291-303}
}