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rdf:type
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Description
| - The objective of the paper is to demonstrate the abilities and possible approaches to classification of set of objects using self-organizing maps. As the objects, clients of an insurance company that made an agreement regarding mandatory insurance of motor vehicles were selected. The opinions of the clients and their overall satisfaction reflected in responses to presented answers. The clients were classified into three groups. The first two contained satisfied clients (i.e. good clients for the company), the last group contained clients that could potentially switch to the competitors. Subsequent analysis enabled discovering the reasons of low customer satisfaction and critical factors of losing the least satisfied clients. For the analysis of the responses (one hundred fifty-one) and the insurance company, experimental model of self-organizing map realized at the Department of informatics was used. Used experimental model has proved very effective software tool.
- The objective of the paper is to demonstrate the abilities and possible approaches to classification of set of objects using self-organizing maps. As the objects, clients of an insurance company that made an agreement regarding mandatory insurance of motor vehicles were selected. The opinions of the clients and their overall satisfaction reflected in responses to presented answers. The clients were classified into three groups. The first two contained satisfied clients (i.e. good clients for the company), the last group contained clients that could potentially switch to the competitors. Subsequent analysis enabled discovering the reasons of low customer satisfaction and critical factors of losing the least satisfied clients. For the analysis of the responses (one hundred fifty-one) and the insurance company, experimental model of self-organizing map realized at the Department of informatics was used. Used experimental model has proved very effective software tool. (en)
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Title
| - Evolution of insurance company service quality survey, using self-learning neural network
- Evolution of insurance company service quality survey, using self-learning neural network (en)
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skos:prefLabel
| - Evolution of insurance company service quality survey, using self-learning neural network
- Evolution of insurance company service quality survey, using self-learning neural network (en)
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skos:notation
| - RIV/62156489:43110/11:00171223!RIV12-MSM-43110___
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http://linked.open...avai/riv/aktivita
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http://linked.open...avai/riv/aktivity
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http://linked.open...iv/cisloPeriodika
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http://linked.open...vai/riv/dodaniDat
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http://linked.open...aciTvurceVysledku
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http://linked.open.../riv/druhVysledku
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http://linked.open...iv/duvernostUdaju
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http://linked.open...titaPredkladatele
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http://linked.open...dnocenehoVysledku
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http://linked.open...ai/riv/idVysledku
| - RIV/62156489:43110/11:00171223
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http://linked.open...riv/jazykVysledku
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http://linked.open.../riv/klicovaSlova
| - classification; representation in plane; insurance company; self organizing; neural network; class representative (en)
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http://linked.open.../riv/klicoveSlovo
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http://linked.open...odStatuVydavatele
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http://linked.open...ontrolniKodProRIV
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http://linked.open...i/riv/nazevZdroje
| - Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis
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http://linked.open...in/vavai/riv/obor
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http://linked.open...ichTvurcuVysledku
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http://linked.open...cetTvurcuVysledku
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http://linked.open...UplatneniVysledku
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http://linked.open...v/svazekPeriodika
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http://linked.open...iv/tvurceVysledku
| - Dvořáková, Dana
- Konečný, Vladimír
- Trenz, Oldřich
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http://linked.open...n/vavai/riv/zamer
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issn
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number of pages
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http://localhost/t...ganizacniJednotka
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