Model for Evaluating the Effectiveness of Search Operations
DOI:
https://doi.org/10.5614/itbj.ict.res.appl.2015.9.2.5Abstract
An automated search with human involvement consisting of twostages is given detailed consideration in this paper. In the first stage, a searchwithout direct human involvement is implemented. In the second stage, thesearch assumes human involvement. Evaluations of the search operations'effectiveness are presented. These operations are implemented for searching oneobject exclusively among a variety of similar objects. The average number ofsimilar objects recommended for further analysis was used as effectivenessindicator. A set of numerical evaluation criteria for search effectiveness isintroduced. The basis of the search block is a pattern recognition algorithmcharacterized by two probabilities: 1) probability of missing a target, and 2) falsealarm probability. An analytical model of the search block was developed. In thispaper particular attention is given to the average length of the recommendatorylist as an effectiveness indicator. Four properties of this indicator weredetermined.
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