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A curated, ontology-based, large-scale knowledge graph of artificial intelligence tasks and benchmarks [article]

Kathrin Blagec, Adriano Barbosa-Silva, Simon Ott, Matthias Samwald
2021 arXiv   pre-print
To help address these issues, we created the Intelligence Task Ontology and Knowledge Graph (ITO), a comprehensive, richly structured and manually curated resource on artificial intelligence tasks, benchmark  ...  Research in artificial intelligence (AI) is addressing a growing number of tasks through a rapidly growing number of models and methodologies.  ...  To help address these issues, we introduce the Intelligence Task Ontology and Knowledge Graph (ITO), a comprehensive, richly structured and manually curated data resource on artificial intelligence tasks  ... 
arXiv:2110.01434v2 fatcat:7btwyxwsczenhjbnmsnzlufvai

Mapping global dynamics of benchmark creation and saturation in artificial intelligence [article]

Adriano Barbosa-Silva, Simon Ott, Kathrin Blagec, Jan Brauner, Matthias Samwald
2022 arXiv   pre-print
We curated data for 1688 benchmarks covering the entire domains of computer vision and natural language processing, and show that a large fraction of benchmarks quickly trended towards near-saturation,  ...  Benchmarks are crucial to measuring and steering progress in artificial intelligence (AI).  ...  Mapping global dynamics of benchmark creation and saturation in artificial intelligence | 23 J.B. gave feedback on the analyses and the manuscript and approved the manuscript.  ... 
arXiv:2203.04592v3 fatcat:xofvglcnrrfvzd5xbiiaz5ogdi

Neuro-Symbolic Techniques for Description Logic Reasoning (Student Abstract)

Gunjan Singh, Sutapa Mondal, Sumit Bhatia, Raghava Mutharaju
2021 AAAI Conference on Artificial Intelligence  
To fill this gap, we propose two approaches: an ontology-based embedding model for theories in EL ++ description logic and a reinforcement learning-based solution for efficient tableau-based reasoning  ...  However, the existing approaches do not take into account the inference capabilities of ontology languages that are based on expressive description logic (such as OWL 2).  ...  To the best of our knowledge, most of the existing work in these directions, mainly cover tasks in the context of knowledge graph (KG) completion and relatively little attention has been paid to utilizing  ... 
dblp:conf/aaai/SinghMBM21 fatcat:k7cngkni75dbbcyf62ghjn5jku

TINKER: A framework for Open source Cyberthreat Intelligence [article]

Nidhi Rastogi, Sharmishtha Dutta, Mohammad Zaki, Alex Gittens, Charu Aggarwal
2022 arXiv   pre-print
The information is extracted and stored in a structured format using knowledge graphs such that the semantics of the threat intelligence can be preserved and shared at scale with other security analysts  ...  Following TINKER, we generate a Cyberthreat Intelligence Knowledge Graph (CTI-KG) and demonstrate the usage using different use cases.  ...  Unlike a small curated benchmark dataset, we require information extraction systems that are scalable and replicable for a large amount of text corpus specific to the cyber threat domain.  ... 
arXiv:2102.05571v5 fatcat:dcwimtrxqfbkjpndoedxyz2on4

Semantic Networks for Engineering Design: A Survey [article]

Ji Han, Serhad Sarica, Feng Shi, Jianxi Luo
2020 arXiv   pre-print
There have been growing uses of semantic networks in the past decade, such as leveraging large-scale pre-trained graph knowledge databases for various natural language processing (NLP) tasks in engineering  ...  Meanwhile, there are emerging efforts to mine large scale technical publication and patent databases to construct engineering-contextualized semantic network databases, e.g., B-Link and TechNet, to support  ...  A semantic network is an artificial associative network representing knowledge in relation patterns of nodes and links interconnected in a graph structure (Sowa, 1992) .  ... 
arXiv:2012.07060v1 fatcat:75wj7nmyhjharbwmqko42l6vri

A critical analysis of metrics used for measuring progress in artificial intelligence [article]

Kathrin Blagec, Georg Dorffner, Milad Moradi, Matthias Samwald
2021 arXiv   pre-print
Comparing model performances on benchmark datasets is an integral part of measuring and driving progress in artificial intelligence.  ...  A model's performance on a benchmark dataset is commonly assessed based on a single or a small set of performance metrics.  ...  Furthermore, we thank Michael Kammer for valuable comments and discussions. 7 https://bioportal.bioontology.org/ontologies/ITO  ... 
arXiv:2008.02577v2 fatcat:u6phhkiwnvclhaksgwqudbpkw4

SEMANTIC NETWORKS FOR ENGINEERING DESIGN: A SURVEY

Ji Han, Serhad Sarica, Feng Shi, Jianxi Luo
2021 Proceedings of the Design Society  
AbstractThere have been growing uses of semantic networks in the past decade, such as leveraging large-scale pre-trained graph knowledge databases for various natural language processing (NLP) tasks in  ...  Meanwhile, there are emerging efforts to mine large scale technical publication and patent databases to construct engineering-contextualized semantic network databases, e.g., B-Link and TechNet, to support  ...  The public pre-trained large-scale technology semantic networks, e.g., TechNet and B-Link, may serve as an infrastructure for a wide range of artificial intelligence applications related to technology  ... 
doi:10.1017/pds.2021.523 fatcat:np2v374bdjcvnkx67qgtnygmlq

A global analysis of metrics used for measuring performance in natural language processing [article]

Kathrin Blagec and Georg Dorffner and Milad Moradi and Simon Ott and Matthias Samwald
2022 arXiv   pre-print
to other tasks and languages.  ...  Here we provide the first large-scale cross-sectional analysis of metrics used for measuring performance in natural language processing.  ...  Acknowledgements We thank the team from 'Papers With Code' for making their database available and all annotators who contributed to it.  ... 
arXiv:2204.11574v1 fatcat:n7jj6zcbevhubja5jtczwbmo7i

Domain-specific Knowledge Graphs: A survey [article]

Bilal Abu-Salih
2021 arXiv   pre-print
Knowledge Graphs (KGs) have made a qualitative leap and effected a real revolution in knowledge representation.  ...  This is leveraged by the underlying structure of the KG which underpins a better comprehension, reasoning and interpretation of knowledge for both human and machine.  ...  of large-scale KGs.  ... 
arXiv:2011.00235v3 fatcat:oc2loewqdjfgvlapy4kmult5li

IMIA LaMB WG event: 'Biomedical Semantics in the Big Data Era', Workshop at MEDINFO 2015 – São Paulo,Brazil

Roland Cornet, Stephane Meystre, Stefan Schulz, Patrick Ruch, Tomasz Adamusiak, Laszlo Balkanyi, Jianying Hu
2019 Zenodo  
and unstructured content , by Tomasz Adamusiak - Summary and workshop organization, by Laszlo Balkanyi (2) a reader with a library of references for the MEDINFO 2015 workshop of IMIA LaMB Working Group  ...  The workshop of IMIA WG 'Language and Meaning in Biomedicine' was held at MEDINFO 2015 – São Paulo,Brazil.  ...  Additionally, we integrated all terminologies into a single UMLS derived ontology and further optimized it to make the relatively large concept graph manageable.  ... 
doi:10.5281/zenodo.3398964 fatcat:ksn3rajzs5earbjd3kczdvrwdi

Discovering meaning on the go in large heterogenous data

Harry Halpin, Fiona McNeill
2013 Artificial Intelligence Review  
When presented with a large, unknown data source, it is very di cult to ascribe meaning to the terms of that data source, and to understand what is being conveyed.  ...  We take a brief look at cutting edge research in this field, summarising four papers published in the special issue of the AI Review on Discovering Meaning on the go in Large Heterogenous Data, and conclude  ...  problems from the standpoint of artificial intelligence."  ... 
doi:10.1007/s10462-012-9377-4 fatcat:zy3swcqdrjbtrdqsjti4mogbmi

Knowledge-based Biomedical Data Science 2019 [article]

Tiffany J. Callahan, Ignacio J. Tripodi Computational Bioscience Program, Department of Pharmacology, University of Colorado Denver Anschutz Medical Campus
2019 arXiv   pre-print
Major themes include the relationships between knowledge graphs and machine learning, the use of natural language processing, and the expansion of knowledge-based approaches to novel domains, such as Chinese  ...  Knowledge-based biomedical data science (KBDS) involves the design and implementation of computer systems that act as if they knew about biomedicine.  ...  SUPPLEMENTAL MATERIAL The full versions of Tables 1-3 are submitted as Supplemental Tables 1-3.  ... 
arXiv:1910.06710v1 fatcat:kvz5k643zvhpdiq67blc2v33wi

Patent Data for Engineering Design: A Critical Review and Future Directions [article]

Shuo Jiang, Serhad Sarica, Binyang Song, Jie Hu, Jianxi Luo
2022 arXiv   pre-print
Patent data have long been used for engineering design research because of its large and expanding size, and widely varying massive amount of design information contained in patents.  ...  Recent advances in artificial intelligence and data science present unprecedented opportunities to develop data-driven design methods and tools, as well as advance design science, using the patent database  ...  , Semantic Network and Knowledge GraphOntology [47, 48] • Semantic network [6, 22, 45, 72] • Automated or semi-automated constructed knowledge graph [4, 37, 39, 40] • Manually curated knowledge  ... 
arXiv:2111.08500v3 fatcat:32uesjowqvgdlfupgig54zpwfu

Structure Discovery in Large Semantic Graphs Using Extant Ontological Scaling and Descriptive Semantics

Sinan al-Saffar, Cliff Joslyn, Alan Chappell
2011 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology  
We then describe a method of ontological scaling in which the ontology is employed as a hierarchical scaling filter to infer different resolution levels at which the graph structures are to be viewed or  ...  We first present the concept of an extant ontology as a statistical description of the semantic relations present amongst the typed entities modeled in the graph.  ...  This model was first developed for artificial intelligence and machine translation [1] , [2] .  ... 
doi:10.1109/wi-iat.2011.241 dblp:conf/webi/Al-SaffarJC11 fatcat:qimqt4jhczbgdl3kctf647iegm

Patent Data for Engineering Design: A Review

S. Jiang, S. Sarica, B. Song, J. Hu, J. Luo
2022 Proceedings of the Design Society  
Recent advances in artificial intelligence and data science present unprecedented opportunities to mine, analyse and make sense of patent data to develop design theory and methodology.  ...  Herein, we survey the patent-for-design literature by their contributions to design theories, methods, tools, and strategies, as well as different forms of patent data and various methods.  ...  ., 2012) or manually curated ontology-based knowledge graphs (Atherton et al., 2018; Hagedorn et al., 2015; Jiang et al., 2018) to support design innovation and problem solving.  ... 
doi:10.1017/pds.2022.74 fatcat:elpgmp2daneqfas3bmb2mv2sgm
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