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Introduction to Information Retrieval Quotes

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Introduction to Information Retrieval Introduction to Information Retrieval by Christopher D. Manning
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Introduction to Information Retrieval Quotes Showing 1-6 of 6
“Here the query A320 returns algorithmic search results about the Airbus aircraft, together with advertisements for various non-aircraft goods numbered A320 that advertisers seek to market to those querying on this query. The lack of advertisements for the aircraft reflects the fact that few marketers attempt to sell A320 aircraft on the web.”
Hinrich Schütze, Introduction to Information Retrieval
“In principle, more analytic power can be achieved by varying multiple things at once in an uncorrelated (random) way, and doing standard analysis, such as multiple linear regression. In practice, though, A/B testing is widely used, because A/B tests are easy to deploy, easy to understand, and easy to explain to management.”
Christopher D. Manning , Introduction to Information Retrieval
“A human is not a device that reliably reports a gold standard judgment of relevance of a document to a query.”
Hinrich Schütze, Introduction to Information Retrieval
tags: 2008, snark
“With limited training data, a more constrained model tends to perform better.”
Christopher d. manning, Introduction to Information Retrieval
“The key utility measure is user happiness. Speed of response and the size of the index are factors in user happiness. It seems reasonable to assume that relevance of results is the most important factor: blindingly fast, useless answers do not make a user happy. However, user perceptions do not always coincide with system designers' notions of quality. For example, user happiness commonly depends very strongly on user interface design issues, including the layout, clarity, and responsiveness of the user interface, which are independent of the quality of the results returned.”
Christopher D. Manning, Introduction to Information Retrieval
“Thus, an index built for vector space retrieval cannot, in general, be used for phrase queries. Moreover, there is no way of demanding a vector space score for a phrase query—we only know the relative weights of each term in a document.”
Prabhakar Raghavan, Introduction to Information Retrieval