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A curated, ontology-based, large-scale knowledge graph of artificial intelligence tasks and benchmarks
[article]
2021
arXiv
pre-print
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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]
2022
arXiv
pre-print
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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)
2021
AAAI Conference on Artificial Intelligence
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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]
2022
arXiv
pre-print
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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]
2020
arXiv
pre-print
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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]
2021
arXiv
pre-print
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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
2021
Proceedings of the Design Society
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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]
2022
arXiv
pre-print
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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]
2021
arXiv
pre-print
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2020 pre-print arXiv:2011.00235v2 fatcat:4b5htecxj5fhxhbinou26nn2uuOther Versions
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
2019
Zenodo
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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
2013
Artificial Intelligence Review
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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]
2019
arXiv
pre-print
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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]
2022
arXiv
pre-print
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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 Graph • Ontology [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
2011
2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology
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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
2022
Proceedings of the Design Society
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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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