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On July 16, 2024 at 11:50:32 AM UTC,
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| 4 | "author": "Mayra Russo", | 4 | "author": "Mayra Russo", | ||
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| 16 | "extra_authors": [ | 16 | "extra_authors": [ | ||
| 17 | { | 17 | { | ||
| 18 | "extra_author": "Yashrajsinh Chudasama", | 18 | "extra_author": "Yashrajsinh Chudasama", | ||
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| 39 | "license_title": "Creative Commons Attribution", | 39 | "license_title": "Creative Commons Attribution", | ||
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| 41 | "link_orkg": "https://www.orkg.org/orkg/paper/R705632", | 41 | "link_orkg": "https://www.orkg.org/orkg/paper/R705632", | ||
| 42 | "maintainer": "Yashrajsinh Chudasama", | 42 | "maintainer": "Yashrajsinh Chudasama", | ||
| 43 | "maintainer_email": "yashrajsinh.chudasama@tib.eu", | 43 | "maintainer_email": "yashrajsinh.chudasama@tib.eu", | ||
| 44 | "metadata_created": "2024-07-16T11:43:50.389008", | 44 | "metadata_created": "2024-07-16T11:43:50.389008", | ||
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| 46 | "name": | 46 | "name": | ||
| 47 | ploying-hybrid-ai-systems-to-trace-and-document-bias-in-ml-pipelines", | 47 | ploying-hybrid-ai-systems-to-trace-and-document-bias-in-ml-pipelines", | ||
| 48 | "notes": "A hybrid AI system capable of identifying bias patterns in | 48 | "notes": "A hybrid AI system capable of identifying bias patterns in | ||
| 49 | datasets used by predictive AI models. The proposed system captures | 49 | datasets used by predictive AI models. The proposed system captures | ||
| 50 | knowledge about dataset characteristics and represents it as factual | 50 | knowledge about dataset characteristics and represents it as factual | ||
| 51 | statements in a knowledge graph.", | 51 | statements in a knowledge graph.", | ||
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| 56 | "approval_status": "approved", | 56 | "approval_status": "approved", | ||
| 57 | "created": "2017-11-23T17:30:37.757128", | 57 | "created": "2017-11-23T17:30:37.757128", | ||
| 58 | "description": "The German National Library of Science and | 58 | "description": "The German National Library of Science and | ||
| 59 | Technology, abbreviated TIB, is the national library of the Federal | 59 | Technology, abbreviated TIB, is the national library of the Federal | ||
| 60 | Republic of Germany for all fields of engineering, technology, and the | 60 | Republic of Germany for all fields of engineering, technology, and the | ||
| 61 | natural sciences.", | 61 | natural sciences.", | ||
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| 68 | "title": "TIB", | 68 | "title": "TIB", | ||
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| 78 | "auto_update": "No", | 78 | "auto_update": "No", | ||
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| 83 | "created": "2024-07-16T11:49:29.885104", | 83 | "created": "2024-07-16T11:49:29.885104", | ||
| 84 | "description": "", | 84 | "description": "", | ||
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| 94 | "name": "Doc-Bias", | 94 | "name": "Doc-Bias", | ||
| 95 | "package_id": "e2d84387-2dfc-43c3-b372-0b23b128a79c", | 95 | "package_id": "e2d84387-2dfc-43c3-b372-0b23b128a79c", | ||
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| 122 | "name": "Doc-Bias", | ||||
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| 110 | "state": "draft", | 138 | "state": "draft", | ||
| 111 | "tags": [ | 139 | "tags": [ | ||
| 112 | { | 140 | { | ||
| 113 | "display_name": "Bias", | 141 | "display_name": "Bias", | ||
| 114 | "id": "2dae510d-16c2-4435-8af9-05771787347f", | 142 | "id": "2dae510d-16c2-4435-8af9-05771787347f", | ||
| 115 | "name": "Bias", | 143 | "name": "Bias", | ||
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| 117 | "vocabulary_id": null | 145 | "vocabulary_id": null | ||
| 118 | }, | 146 | }, | ||
| 119 | { | 147 | { | ||
| 120 | "display_name": "knowledge graphs", | 148 | "display_name": "knowledge graphs", | ||
| 121 | "id": "6a8020fc-d07a-4f67-9d12-74c252ba1c81", | 149 | "id": "6a8020fc-d07a-4f67-9d12-74c252ba1c81", | ||
| 122 | "name": "knowledge graphs", | 150 | "name": "knowledge graphs", | ||
| 123 | "state": "active", | 151 | "state": "active", | ||
| 124 | "vocabulary_id": null | 152 | "vocabulary_id": null | ||
| 125 | }, | 153 | }, | ||
| 126 | { | 154 | { | ||
| 127 | "display_name": "machine learning", | 155 | "display_name": "machine learning", | ||
| 128 | "id": "9e42784b-6ee7-47e8-a69a-28b8c510212b", | 156 | "id": "9e42784b-6ee7-47e8-a69a-28b8c510212b", | ||
| 129 | "name": "machine learning", | 157 | "name": "machine learning", | ||
| 130 | "state": "active", | 158 | "state": "active", | ||
| 131 | "vocabulary_id": null | 159 | "vocabulary_id": null | ||
| 132 | } | 160 | } | ||
| 133 | ], | 161 | ], | ||
| 134 | "temporal_resolution": "", | 162 | "temporal_resolution": "", | ||
| 135 | "title": "Employing Hybrid AI Systems to Trace and Document Bias in | 163 | "title": "Employing Hybrid AI Systems to Trace and Document Bias in | ||
| 136 | ML Pipelines", | 164 | ML Pipelines", | ||
| 137 | "type": "dataset", | 165 | "type": "dataset", | ||
| 138 | "url": | 166 | "url": | ||
| 139 | ps://github.com/SDM-TIB/DocBiasKG/tree/main/DocBias_over_InterpretME", | 167 | ps://github.com/SDM-TIB/DocBiasKG/tree/main/DocBias_over_InterpretME", | ||
| 140 | "version": "", | 168 | "version": "", | ||
| 141 | "version_note": "" | 169 | "version_note": "" | ||
| 142 | } | 170 | } |