An information retrieval benchmarking model of satisficing and impatient users' behavior in online search environments

D Di Caprio, FJ Santos-Arteaga, M Tavana - Expert Systems with …, 2022 - Elsevier
This study analyzes the effects that the position of the alternatives ranked by a search
engine and the relative impatience of users have on their information retrieval behavior. We …

A click-through rate model of e-commerce based on user interest and temporal behavior

Y **ao, WK He, Y Zhu, J Zhu - Expert Systems with Applications, 2022 - Elsevier
In the advertising and marketing of e-commerce platform, click rate prediction is directly
related to the revenue of e-commerce platform. In this paper, we propose an advertising click …

Interpretable click-through rate prediction through distillation of the neural additive factorization model

A Jose, SD Shetty - Information Sciences, 2022 - Elsevier
An accurate estimation of the click-through rate (CTR), that is, the probability of clicking on a
recommended advertisement item online, is crucial for advertising agencies to make …

[HTML][HTML] On the capacity of artificial intelligence techniques and statistical methods to deal with low-quality data in medical supply chain environments

FJS Arteaga, D Di Caprio, M Tavana… - … Applications of Artificial …, 2024 - Elsevier
We illustrate the capacity of Artificial Intelligence (AI) and Machine Learning (ML) techniques
to preserve consistent categorization abilities whenever the quality of the data decreases …

[HTML][HTML] Rational satisficing heuristics as determinants of online search behavior

D Di Caprio, FJ Santos-Arteaga - International Journal of Information …, 2024 - Elsevier
We design a set of satisficing heuristic algorithms that mimic the online information retrieval
behavior of rational decision makers (DMs) as reflected in their click through rates (CTRs) …

DistilledCTR: Accurate and scalable CTR prediction model through model distillation

A Jose, SD Shetty - Expert Systems with Applications, 2022 - Elsevier
Accuracy and scalability are critical to the efficiency and effectiveness of real-time
recommender systems. Recent deep learning-based click-through rate prediction models …

Hierarchical attention and feature projection for click-through rate prediction

J Zhang, C Zhong, S Fan, X Mu, Z Ni - Applied Intelligence, 2022 - Springer
Click-through rate (CTR) prediction plays an important role in many industrial applications,
feature engineering directly influences CTR prediction performance because features are …

ESWA an information retrieval benchmarking model of satisficing and impatient users' behavior in online search environments [Source Code]

D Di Caprio, FJS Arteaga… - Expert Systems with …, 2021 - produccioncientifica.ucm.es
This study analyzes the effects that the position of the alternatives ranked by a search
engine and the relative impatience of users have on their information retrieval behavior. We …

Comparative Analysis of Ad Click Behavior Prediction Using GAN-Augmented Data and Traditional Machine Learning Techniques

AS Salıhı, O Yıldız - Politeknik Dergisi - dergipark.org.tr
In e-commerce, predicting click-through rates (CTR) is crucial to anticipate user behavior.
User historical data can be used to extract interests and enhance CTR prediction, leading to …