STAR: Semantic Temporal Associative Retrieval - A Local-First Graph-Based Context Engine

Fuente: Zenodo

Gespeichert in:

Bibliographische Detailangaben
1. Verfasser:	Balch II, R.S.
Format:	Recurso digital
Veröffentlicht:	Zenodo 2026
Schlagworte:	information retrieval graph algorithms local-first AI personal knowledge management sparse retrieval
Online-Zugang:	Acceder al recurso
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

_version_	1866901749516730368
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