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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Predicting Information Retrieval Performance

Predicting Information Retrieval Performance

Losee, Robert M.

Paperback

Series: Synthesis Lectures on Information Concepts, Retrieval, and S

General ComputersSystem Administration

ISBN10: 3031011899
ISBN13: 9783031011894
Publisher: Springer Nature
Published: Dec 19 2018
Pages: 59
Weight: 0.34
Height: 0.17 Width: 7.50 Depth: 9.25
Language: English

Information Retrieval performance measures are usually retrospective in nature, representing the effectiveness of an experimental process. However, in the sciences, phenomena may be predicted, given parameter values of the system. After developing a measure that can be applied retrospectively or can be predicted, performance of a system using a single term can be predicted given several different types of probabilistic distributions. Information Retrieval performance can be predicted with multiple terms, where statistical dependence between terms exists and is understood. These predictive models may be applied to realistic problems, and then the results may be used to validate the accuracy of the methods used. The application of metadata or index labels can be used to determine whether or not these features should be used in particular cases. Linguistic information, such as part-of-speech tag information, can increase the discrimination value of existing terminology and can be studied predictively.

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