QAnswer: Towards Question Answering Search over Websites

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.

References in corpus (3)

• ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT
• Retrieving and Reading: A Comprehensive Survey on Open-domain Question Answering
• Introduction to Neural Network based Approaches for Question Answering over Knowledge Graphs

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