Example-Driven Query Intent Discovery: Abductive Reasoning using Semantic Similarity
Summary: SQUID extends QBE to semantic similarity, solving intent via abductive reasoning over open-world data to auto-create SPJ queries. Precomputed semantic properties in abduction-ready DBs enable inference, yielding accurate intents and outperforming baselines. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Anna Fariha (University of Massachusetts Amherst)
- 2. Alexandra Meliou (University of Massachusetts Amherst)
BibTeX Citation
@article{fariha_vldb19,
title = {{Example-Driven Query Intent Discovery: Abductive Reasoning using Semantic Similarity}},
author = {Fariha, Anna and Meliou, Alexandra},
journal = {PVLDB},
series = {{VLDB} '19},
volume = {12},
number = {11},
pages = {1262--1275},
doi = {10.14778/3342263.3342266},
url = {https://doi.org/10.14778/3342263.3342266},
year = {2019}
}
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|---|---|---|---|---|
| 1 | 4,671 | PreQR: Pre-training Representation for SQL Understanding | 2022 | SIGMOD |
| 2 | 8,987 | Constructing Expressive Relational Queries with Dual-Specification Synthesis | 2020 | CIDR |
| 3 | 9,353 | On Efficient Approximate Queries over Machine Learning Models | 2023 | VLDB |
| 4 | 10,486 | Qualitative Join Discovery in Data Lakes using Examples | 2026 | SIGMOD |
| 5 | 9,149 | Semantic SPARQL Similarity Search Over RDF Knowledge Graphs | 2016 | VLDB |
| 6 | 2,832 | Expressive and Flexible Access to Web-Extracted Data: A Keyword-based Structured Query Language | 2010 | SIGMOD |
| 7 | 1,922 | QUEST: A Keyword Search System for Relational Data based on Semantic and Machine Learning Techniques | 2013 | VLDB |
| 8 | 4,372 | Schemaless and Structureless Graph Querying | 2014 | VLDB |
| 9 | 4,131 | Querying Complex Structured Databases | 2007 | VLDB |
| 10 | 9,368 | SQuID: Semantic Similarity-Aware Query Intent Discovery | 2018 | SIGMOD |