How Does Search Find an Answer So Quickly?

How Does Search Find an Answer So Quickly? · 1:37 · Intellect Plus

In short: From medieval indexes and the Library of Congress card drawers to word weighting, link-based ranking and learned retrieval, a short history of how answers are found and ordered, and of the trade-offs and questions still open.

A 1:37 short film in the series “From Fingers to Qubits”, narrated by intellect_voice_01.

Sources used in this film: Library of Congress (Research Guides), “Research Guides: The Library of Congress Card Catalog: Origins and Development of the Card Catalog”; National Institute of Standards and Technology (NIST), “Text REtrieval Conference (TREC)”; arXiv (Cornell University), preprint of a paper presented at EMNLP 2020, “Dense Passage Retrieval for Open-Domain Question Answering”; Academia.edu (hosting Larry Page, 'The PageRank Citation Ranking: Bringing Order to the Web', ilpubs.stanford.edu, 1999), “The PageRank Citation Ranking: Bringing Order to the Web”; Academia.edu (hosted copy of the survey 'The Probabilistic Relevance Framework: BM25 and Beyond'), “The Probabilistic Relevance Framework: BM25 and Beyond”; now Publishers (Foundations and Trends series), hosted on IEEE Xplore, “The Probabilistic Relevance Framework | now eBooks | IEEE Xplore”; arXiv (Cornell University); survey by Jimmy Lin et al., published as a volume in Morgan & Claypool's Synthesis Lectures on Human Language Technologies, “Pretrained Transformers for Text Ranking: BERT and Beyond”; Springer Nature (Springer Cham), book overview page for Lin, Nogueira & Yates, 'Pretrained Transformers for Text Ranking: BERT and Beyond' (Synthesis Lectures on Human Language Technologies), “Pretrained Transformers for Text Ranking”; Washington Independent Review of Books (review by Peggy Kurkowski of Dennis Duncan's 'Index, A History of the'), “Index, A History of the: A Bookish Adventure from Medieval Manuscripts to the Digital Age | Washington Independent Review of Books”.

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