Bew: Towards Answering Business-Entity-Related Web Questions

TL;DR

BewQA is a system designed to answer business-related web questions by automatically extracting webpage templates and guiding search, significantly outperforming existing QA models and search engines in accuracy.

Contribution

The paper introduces a novel template-based approach for answering dynamic, business-related questions without requiring training, leveraging aggregator websites for template extraction.

Findings

27% improvement in F1 score over state-of-the-art QA models

29% more correct answers than a commercial search engine

Crowdsourced dataset of 1066 Bew questions in the restaurant domain

Abstract

We present BewQA, a system specifically designed to answer a class of questions that we call Bew questions. Bew questions are related to businesses/services such as restaurants, hotels, and movie theaters; for example, "Until what time is happy hour?". These questions are challenging to answer because the answers are found in open-domain Web, are present in short sentences without surrounding context, and are dynamic since the webpage information can be updated frequently. Under these conditions, existing QA systems perform poorly. We present a practical approach, called BewQA, that can answer Bew queries by mining a template of the business-related webpages and using the template to guide the search. We show how we can extract the template automatically by leveraging aggregator websites that aggregate information about business entities in a domain (e.g., restaurants). We answer a given question by identifying the section from the extracted template that is most likely to contain the answer. By doing so we can extract the answers even when the answer span does not have sufficient context. Importantly, BewQA does not require any training. We crowdsource a new dataset of 1066 Bew questions and ground-truth answers in the restaurant domain. Compared to state-of-the-art QA models, BewQA has a 27 percent point improvement in F1 score. Compared to a commercial search engine, BewQA answered correctly 29% more Bew questions.