# Subjective Databases

arXiv: https://arxiv.org/abs/1902.09661 · HTML: https://mlsanity.com/paper/1902.09661/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 25 Feb 2019.

## Built on by (most cited first, 7 of 7)

- [VerifAI: Verified Generative AI](https://mlsanity.com/paper/2307.02796/) (2023)
- [Product Question Answering in E-Commerce: A Survey](https://mlsanity.com/paper/2302.08092/) (2023)
- [Is the House Ready For Sleeptime? Generating and Evaluating Situational Queries for Embodied Question Answering](https://mlsanity.com/paper/2405.04732/) (2024)
- [It's the Same Old Story! Enriching Event-Centric Knowledge Graphs by Narrative Aspects](https://mlsanity.com/paper/2205.03876/) (2022)
- [Towards Multi-Modal DBMSs for Seamless Querying of Texts and Tables](https://mlsanity.com/paper/2304.13559/) (2023)
- [Towards Temporal Knowledge-Base Creation for Fine-Grained Opinion Analysis with Language Models](https://mlsanity.com/paper/2509.02363/) (2025)
- [Commonsense Knowledge Base Construction in the Age of Big Data](https://mlsanity.com/paper/2105.01925/) (2021)

## Abstract (arXiv)

Online users are constantly seeking experiences, such as a hotel with clean rooms and a lively bar, or a restaurant for a romantic rendezvous. However, e-commerce search engines only support queries involving objective attributes such as location, price, and cuisine, and any experiential data is relegated to text reviews. In order to support experiential queries, a database system needs to model subjective data and also be able to process queries where the user can express varied subjective experiences in words chosen by the user, in addition to specifying predicates involving objective attributes. This paper introduces Opine, a subjective database system that addresses these challenges. We introduce a data model for subjective databases. We describe how Opine translates subjective queries against the subjective database schema, which is done by matching the user query phrases to the underlying schema. We also show how the experiential conditions specified by the user can be combined and the results aggregated and ranked. We demonstrate that subjective databases satisfy user needs more effectively and accurately than alternative techniques through experiments with real data of hotel and restaurant reviews.