# QAnswer: Towards Question Answering Search over Websites

Source: [QAnswer: Towards Question Answering Search over Websites](<https://www.sota2.com/research/paper/68fa71df1e209131cea537ca>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-26T02:14:27.865Z

Authors: Kunpeng Guo, Clement Defretiere, Dennis Diefenbach, Christophe Gravier, Antoine Gourru

Published: 2024-01-17T12:31:45.000Z

## Abstract

Question Answering (QA) is increasingly used by search engines to provide results to their end-users, yet very few websites currently use QA technologies for their search functionality. To illustrate the potential of QA technologies for the website search practitioner, we demonstrate web searches that combine QA over knowledge graphs and QA over free text -- each being usually tackled separately. We also discuss the different benefits and drawbacks of both approaches for web site searches. We use the case studies made of websites hosted by the Wikimedia Foundation (namely Wikipedia and Wikidata). Differently from a search engine (e.g. Google, Bing, etc), the data are indexed integrally, i.e. we do not index only a subset, and they are indexed exclusively, i.e. we index only data available on the corresponding website.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2401.09175>)

[PDF](<https://arxiv.org/pdf/2401.09175.pdf>)