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| Formato: | Recurso digital |
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Zenodo
2026
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| Acceso en línea: | https://doi.org/10.5281/zenodo.19324840 |
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| _version_ | 1866901749516730368 |
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| author | Balch II, R.S. |
| author_facet | Balch II, R.S. |
| contents | STAR (Semantic Temporal Associative Retrieval) is a local-first, graph-based information retrieval system designed to enable resource-constrained devices to navigate large-scale personal knowledge corpora. Unlike traditional dense vector retrieval systems that require loading complete indices into RAM, STAR implements a sparse bipartite graph approach that retrieves only relevant 'atoms' of information required for a given query. |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_19324840 |
| institution | Zenodo |
| language | |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | STAR: Semantic Temporal Associative Retrieval - A Local-First Graph-Based Context Engine Balch II, R.S. information retrieval graph algorithms local-first AI personal knowledge management sparse retrieval STAR (Semantic Temporal Associative Retrieval) is a local-first, graph-based information retrieval system designed to enable resource-constrained devices to navigate large-scale personal knowledge corpora. Unlike traditional dense vector retrieval systems that require loading complete indices into RAM, STAR implements a sparse bipartite graph approach that retrieves only relevant 'atoms' of information required for a given query. |
| title | STAR: Semantic Temporal Associative Retrieval - A Local-First Graph-Based Context Engine |
| topic | information retrieval graph algorithms local-first AI personal knowledge management sparse retrieval |
| url | https://doi.org/10.5281/zenodo.19324840 |