Bounded Semantic Interpretation for Reliable Hybrid Product Search
Year: 2026
Type: preprint
Abstract: Product search must reconcile noisy natural-language queries with structured catalogs, exact compatibility constraints, rapidly changing inventory, biased behavioral signals, and strict serving budgets. This systems perspective proposes Bounded Semantic Interpretation (BSI), a hybrid search architecture in which generative models may propose typed intent and attribute hypotheses but cannot directly create catalog facts or bypass deterministic validation. The design combines lexical, dense, learned-sparse, multimodal, and graph-based candidate generation with provenance-preserving fusion and staged re-ranking. It also defines explicit fallback behavior, constraint checks, observability requirements, and release gates. The contribution is architectural and methodological rather than empirical: no production performance claims are made. A reproducible public-benchmark protocol is specified using the Shopping Queries Dataset and the Shopping Queries Image Dataset, together with latency, constraint-violation, robustness, calibration, and subgroup-reliability measures. The framework is intended to help engineering teams test whether semantic improvements remain reliable under operational and governance constraints, and to make failure modes visible before online deployment.
Author: Lara, Mayank
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7203910892
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