
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.
graph algorithms, personal knowledge management, information retrieval, local-first AI, sparse retrieval
graph algorithms, personal knowledge management, information retrieval, local-first AI, sparse retrieval
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
