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Naslov:Click-through rate estimation using CHAID classification tree model : case study of direct benefit transfer in India
Avtorji:ID Gupta, Rajan (Avtor)
ID Pal, Saibal K. (Avtor)
Datoteke:URL https://doi.org/10.1007/978-981-13-1208-3_5
 
Jezik:Angleški jezik
Vrsta gradiva:Neznano
Tipologija:1.08 - Objavljeni znanstveni prispevek na konferenci
Organizacija:UNG - Univerza v Novi Gorici
Opis:Click-Through Rate (CTR) is referred to as the number of clicks on a particular advertisement as compared to the number of impressions on it. It is an important measure to find the effectiveness of any online advertising campaign. The effectiveness of online advertisements through calculations of ROI can be done through the measurement of CTR. There are multiple ways of detecting CTR in past; however, this study focuses on machine learning based classification model. Important parameters are judged on the basis of user behavior toward online ads and CHAID tree model is used to classify the pattern for successful and unsuccessful clicks. The model is implemented using SPSS version 21.0. The dataset used for the testing has been taken from Kaggle website as the data is from anonymous company’s ad campaign given to Kaggle for research purpose. A total of 83.8% accuracy is reported for the classification model used. This implies that CHAID can be used for less critical problems where very high stakes are not involved. This study is useful for online marketers and analytics professionals for assessing the CHAID model’s performance in online advertising world.
Ključne besede:click-through rate, online advertisements, classification tree, mobile ads, click estimation
Leto izida:2019
Št. strani:Str. 45-58
PID:20.500.12556/RUNG-6417 Novo okno
COBISS.SI-ID:58221571 Novo okno
UDK:004
DOI:10.1007/978-981-13-1208-3_5 Novo okno
NUK URN:URN:SI:UNG:REP:CSJA8BFV
Datum objave v RUNG:02.04.2021
Število ogledov:1594
Število prenosov:14
Metapodatki:XML RDF-CHPDL DC-XML DC-RDF
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Gradivo je del monografije

Naslov:Advances in analytics and applications
Uredniki:Arnab Kumar Laha
Kraj izida:Singapore
Založnik:Springer Nature
ISBN:978-981-13-1208-3
COBISS.SI-ID:58217219 Novo okno
Naslov zbirke:Springer proceedings in business and economics (Online)
ISSN zbirke:2198-7254

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