finding
active
finding:simple-experiments-with-an-in-memory-sqlite-database-suggest-dynamic-binding-operations-take-several-orders-of-magnitude-longer-than-a-dedicated-language-runtime-support-librarySimple experiments with an in-memory Sqlite database suggest dynamic binding operations take several orders of magnitude longer than a dedicated language runtime support library.
Empirical observation that a relational engine is too slow for associative lookup, motivating specialized implementation.
Neighborhood — ranked by edge-count
Claims (1)
claim
- Claim that the model has value as a semantic analysis tool even without performance gains.
Questions (1)
question
- whether the mechanisms described in this paper can be efficiently supported by a relational database engineanswered_bygatesQuestion raised about the feasibility of using a relational backend, answered by the Sqlite experiment.
Related by similarity (8)
cosine ≥ 0.65 · no typed edgeEntities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.
- Dynamic programming languages seem to spend much of their time looking up behaviour associatively.claim0.751An observation motivating the associative model as a unifying primitive.
- The central research question explored, by way of examples, throughout the paper.
- Claim that hardware-supported associative lookup would enable high-performance dynamic language runtimes.
- Observation from practical experience with DNA sequence comparison.
- Claim linking late-binding to enhanced runtime adaptability.
- We hope that programs using performatives will be easier to write, understand, debug, modify and (above all) verify.hypothesis0.735Hope expressed about the benefits of Elephant-style programs.
- Critique that Parlog's abstraction level is too high and restrictive.