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CX DB8: A queryable extractive summarizer and semantic search engine

2020-12-07 05:37:32
Allen Roush
arXiv_CL
       
Abstract

Competitive Debate's increasingly technical nature has left competitors looking for tools to accelerate evidence production. We find that the unique type of extractive summarization performed by competitive debaters - summarization with a bias towards a particular target meaning - can be performed using the latest innovations in unsupervised pre-trained text vectorization models. We introduce CX_DB8, a queryable word-level extractive summarizer and evidence creation framework, which allows for rapid, biasable summarization of arbitarily sized texts. CX_DB8s usage of the embedding framework Flair means that as the underlying models improve, CX_DB8 will also improve. We observe that CX_DB8 also functions as a semantic search engine, and has application as a supplement to traditional "find" functionality in programs and webpages. CX_DB8 is currently used by competitive debaters and is made available to the public at this https URL

Abstract (translated)

URL

https://arxiv.org/abs/2012.03942

PDF

https://arxiv.org/pdf/2012.03942.pdf

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