sources.db•45.1 kB
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73�indexidx_entity_links_namesource_entity_linksCREATE INDEX idx_entity_links_name ON source_entity_links(entity_name)r =%�indexidx_source_notes_createdsource_notes
CREATE INDEX idx_source_notes_created ON source_notes(created_at)W1qindexidx_sources_statussources CREATE INDEX idx_sources_status ON sources(status)Q-iindexidx_sources_typesourcesCREATE INDEX idx_sources_type ON sources(type)�M33�Atablesource_entity_linkssource_entity_linksCREATE TABLE source_entity_links (
source_id TEXT REFERENCES sources(id),
entity_name TEXT,
relation_type TEXT CHECK(relation_type IN ('discusses', 'introduces', 'extends', 'evaluates', 'applies', 'critiques')),
notes TEXT,
PRIMARY KEY (source_id, entity_name)
)EY3 indexsqlite_autoindex_source_entity_links_1source_entity_links�%%�Gtablesource_notessource_notesCREATE TABLE source_notes (
source_id TEXT REFERENCES sources(id),
note_title TEXT NOT NULL,
content TEXT NOT NULL,
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY (source_id, note_title)
)7K% indexsqlite_autoindex_source_notes_1source_notes��ctablesourcessourcesCREATE TABLE sources (
id TEXT PRIMARY KEY, -- Using TEXT for UUID storage
title TEXT NOT NULL,
type TEXT CHECK(type IN ('paper', 'webpage', 'book', 'video', 'blog')) NOT NULL,
identifiers TEXT NOT NULL, -- JSON string storing {type: value} pairs
status TEXT CHECK(status IN ('unread', 'reading', 'completed', 'archived')) DEFAULT 'unread'
)-A indexsqlite_autoindex_sources_1sources
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E �fU�/�G055ab11d-2478-48d7-a484-d6b4208e905dTRON: Transformer Neural Network Acceleration with Non-Coherent Silicon Photonicspaper{"semantic_scholar":"3d2b67d34b2cea6d8e58514e2c823abbbabf7f03","doi":"10.1145/example.12345"}reading�bU�9�589bed6e6-b3fb-44d6-97bb-58086e782797EEG emotion recognition using attention-based convolutional transformer neural networkpaper{"semantic_scholar":"4bb4c86761d88d6a3fceae6bc95c10c505db4cc9","arxiv":"2305.12345"}reading tU��
93a764cd-4dde-4672-a637-b878ce0ed05cA Wide and Deep Transformer Neural Network for 12-Lead ECG Classifica�[U��A93a764cd-4dde-4672-a637-b878ce0ed05cA Wide and Deep Transformer Neural Network for 12-Lead ECG Classificationpaper{"semantic_scholar":"d74e87287c845171b58c18bfcdf05ad7895acb19","isbn":"978-0-12-345678-9"}reading�]U��G51bc0790-01e7-4e60-9aa2-d8e094cd98d5Double-head transformer neural network for molecular property predictionpaper{"semantic_scholar":"8d85c22e00c5b26b12b631a6b5a4d2cfb1c56067","doi":"10.1007/example.54321"}reading�nU�7�Oa1bbcdd7-c2e9-4f41-9015-f34b79119135Predicting High-Frequency Stock Movement with Differential Transformer Neural Networkpaper{"semantic_scholar":"4d6be3ebe772e98932d00992a68ec852e78078a9","url":"https://example.com/paper"}reading
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o� � U1�393a764cd-4dde-4672-a637-b878ce0ed05cMedical TechnologyExplores transformer neural network for ECG classification2024-12-28 13:41:11�&U9�3351bc0790-01e7-4e60-9aa2-d8e094cd98d5Molecular Science NoteDemonstrates transformer neural network approach to predicting molecular properties2024-12-28 13:41:11�U7� 3a1bbcdd7-c2e9-4f41-9015-f34b79119135Financial ApplicationApplies transformer neural networks to stock market prediction2024-12-28 13:41:11� U1�/3055ab11d-2478-48d7-a484-d6b4208e905dTechnical InsightsInvestigates hardware acceleration of transformer neural networks using photonics2024-12-28 13:41:11�#U-�9389bed6e6-b3fb-44d6-97bb-58086e782797Research SummaryExplores using transformer neural networks for emotion recognition through EEG signals2024-12-28 13:41:11
� ��@ ;U193a764cd-4dde-4672-a637-b878ce0ed05cMedical Technology?U951bc0790-01e7-4e60-9aa2-d8e094cd98d5Molecular Science Note>U7a1bbcdd7-c2e9-4f41-9015-f34b79119135Financial Application;U1055ab11d-2478-48d7-a484-d6b4208e905dTechnical Insights8U- 89bed6e6-b3fb-44d6-97bb-58086e782797Research Summary
� �^ oUCQ89bed6e6-b3fb-44d6-97bb-58086e782797Transformer Neural NetworksdiscussesUpdated to provide broader context� I; 89bed6e6-b3fb-44d6-97bb-58086e782797EEG Emotion RecognitionextendsGU7 055ab11d-2478-48d7-a484-d6b4208e905dHardware Accelerationevaluates MC 89bed6e6-b3fb-44d6-97bb-58086e782797Transformer Neural Networksapplies
q q�� @U;89bed6e6-b3fb-44d6-97bb-58086e782797EEG Emotion Recognition>U7055ab11d-2478-48d7-a484-d6b4208e905dHardware AccelerationCUC 89bed6e6-b3fb-44d6-97bb-58086e782797Transformer Neural Networks
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} ����} 32024-12-28 13:41:1132024-12-28 13:41:1132024-12-28 13:41:1132024-12-28 13:41:113 2024-12-28 13:41:11
� ��� ;EEG Emotion Recognition7Hardware AccelerationC Transformer Neural Networks