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02850aam a2200325Ki 4500 001 F9A9D8B8101A11EA8DA14E4D97128E48 003 SILO 005 20191126010151 008 190102s2019 caua b 000 0 eng d 020 $a 1681734729 020 $a 9781681734729 020 $a 1681734745 020 $a 9781681734743 035 $a (OCoLC)1080545830 040 $a YDX $b eng $e rda $c YDX $d YDXIT $d UtOrBLW $d SILO 050 4 $a ZA3075 $b .L676 2019 $0 http://id.loc.gov/authorities/classification/Z 082 04 $a 028.7071 $2 23 100 1 $a Losee, Robert M. $q (Robert MacLean), $d 1952- $e author. $0 http://id.loc.gov/authorities/names/n89103171 245 10 $a Predicting information retrieval performance / $c Robert M. Losee. 264 1 $a [San Rafael, California] : $b Morgan & Claypool Publishers, $c [2019] 300 $a xix, 59 pages ; $c 24 cm. 490 1 $a Synthesis lectures on information concepts, retrieval, and services, $x 1947-9468 ; $v #65 504 $a Includes bibliographical references. 520 3 $a 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. This work provides methods for measuring performance that may be used predictively. Means of predicting these performance measures are provided, both for the simple case of a single term in the query and for multiple terms. Methods of applying these formulae are also suggested. 650 0 $a Information retrieval $x Evaluation. 776 08 $i Electronic version: $a Losee, Robert M. (Robert MacLean), 1952- $t Predicting information retrieval performance. $d [San Rafael, California] : Morgan & Claypool Publishers, [2019] $z 1681734737 $w (OCoLC)1080937311 830 0 $a Synthesis lectures on information concepts, retrieval, and services ; $v #65. $0 http://id.loc.gov/authorities/names/no2009051886 941 $a 1 952 $l OVUX522 $d 20191213023020.0 956 $a http://locator.silo.lib.ia.us/search.cgi?index_0=id&term_0=F9A9D8B8101A11EA8DA14E4D97128E48Initiate Another SILO Locator Search